Processing Parameters Optimization for Material Deposition Efficiency in Laser Metal Deposited Titanium Alloy

NASA Astrophysics Data System (ADS)

Mahamood, Rasheedat M.; Akinlabi, Esther T.

2016-03-01

Ti6Al4V is an important Titanium alloy that is mostly used in many applications such as: aerospace, petrochemical and medicine. The excellent corrosion resistance property, the high strength to weight ratio and the retention of properties at high temperature makes them to be favoured in most applications. The high cost of Titanium and its alloys makes their use to be prohibitive in some applications. Ti6Al4V can be cladded on a less expensive material such as steel, thereby reducing cost and providing excellent properties. Laser Metal Deposition (LMD) process, an additive manufacturing process is capable of producing complex part directly from the 3-D CAD model of the part and it also has the capability of handling multiple materials. Processing parameters play an important role in LMD process and in order to achieve desired results at a minimum cost, then the processing parameters need to be properly controlled. This paper investigates the role of processing parameters: laser power, scanning speed, powder flow rate and gas flow rate, on the material utilization efficiency in laser metal deposited Ti6Al4V. A two-level full factorial design of experiment was used in this investigation, to be able to understand the processing parameters that are most significant as well as the interactions among these processing parameters. Four process parameters were used, each with upper and lower settings which results in a combination of sixteen experiments. The laser power settings used was 1.8 and 3 kW, the scanning speed was 0.05 and 0.1 m/s, the powder flow rate was 2 and 4 g/min and the gas flow rate was 2 and 4 l/min. The experiments were designed and analyzed using Design Expert 8 software. The software was used to generate the optimized process parameters which were found to be laser power of 3.2 kW, scanning speed of 0.06 m/s, powder flow rate of 2 g/min and gas flow rate of 3 l/min.

Optimization of process parameters in welding of dissimilar steels using robot TIG welding

NASA Astrophysics Data System (ADS)

Navaneeswar Reddy, G.; VenkataRamana, M.

2018-03-01

Robot TIG welding is a modern technique used for joining two work pieces with high precision. Design of Experiments is used to conduct experiments by varying weld parameters like current, wire feed and travelling speed. The welding parameters play important role in joining of dissimilar stainless steel SS 304L and SS430. In this work, influences of welding parameter on Robot TIG Welded specimens are investigated using Response Surface Methodology. The Micro Vickers hardness tests of the weldments are measured. The process parameters are optimized to maximize the hardness of the weldments.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

NASA Astrophysics Data System (ADS)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global-scale Bayesian calibration of wetland emission models.

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2017-05-01

An important source of uncertainty, which causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. Therefore, finding a subset among numerous physical parameters in numerical models in the atmospheric and oceanic sciences, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach in China. The results imply that nonlinear interactions among parameters play a key role in the identification of sensitive parameters in arid and semi-arid regions of China compared to those in northern, northeastern, and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Process Parameter Optimization for Wobbling Laser Spot Welding of Ti6Al4V Alloy

NASA Astrophysics Data System (ADS)

Vakili-Farahani, F.; Lungershausen, J.; Wasmer, K.

Laser beam welding (LBW) coupled with "wobble effect" (fast oscillation of the laser beam) is very promising for high precision micro-joining industry. For this process, similarly to the conventional LBW, the laser welding process parameters play a very significant role in determining the quality of a weld joint. Consequently, four process parameters (laser power, wobble frequency, number of rotations within a single laser pulse and focused position) and 5 responses (penetration, width, heat affected zone (HAZ), area of the fusion zone, area of HAZ and hardness) were investigated for spot welding of Ti6Al4V alloy (grade 5) using a design of experiments (DoE) approach. This paper presents experimental results showing the effects of variating the considered most important process parameters on the spot weld quality of Ti6Al4V alloy. Semi-empirical mathematical models were developed to correlate laser welding parameters to each of the measured weld responses. Adequacies of the models were then examined by various methods such as ANOVA. These models not only allows a better understanding of the wobble laser welding process and predict the process performance but also determines optimal process parameters. Therefore, optimal combination of process parameters was determined considering certain quality criteria set.

Grey Relational Analysis Coupled with Principal Component Analysis for Optimization of Stereolithography Process to Enhance Part Quality

NASA Astrophysics Data System (ADS)

Raju, B. S.; Sekhar, U. Chandra; Drakshayani, D. N.

2017-08-01

The paper investigates optimization of stereolithography process for SL5530 epoxy resin material to enhance part quality. The major characteristics indexed for performance selected to evaluate the processes are tensile strength, Flexural strength, Impact strength and Density analysis and corresponding process parameters are Layer thickness, Orientation and Hatch spacing. In this study, the process is intrinsically with multiple parameters tuning so that grey relational analysis which uses grey relational grade as performance index is specially adopted to determine the optimal combination of process parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively desired. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of process parameters. Hence, this confirm that the proposed approach in this study can be an useful tool to improve the process parameters in stereolithography process, which is very useful information for machine designers as well as RP machine users.

EVALUATING THE SENSITIVITY OF A SUBSURFACE MULTICOMPONENT REACTIVE TRANSPORT MODEL WITH RESPECT TO TRANSPORT AND REACTION PARAMETERS

EPA Science Inventory

The input variables for a numerical model of reactive solute transport in groundwater include both transport parameters, such as hydraulic conductivity and infiltration, and reaction parameters that describe the important chemical and biological processes in the system. These pa...

Laser Ablatin of Dental Hard Tissue

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seka, W.; Rechmann, P.; Featherstone, J.D.B.

This paper discusses ablation of dental hard tissue using pulsed lasers. It focuses particularly on the relevant tissue and laser parameters and some of the basic ablation processes that are likely to occur. The importance of interstitial water and its phase transitions is discussed in some detail along with the ablation processes that may or may not directly involve water. The interplay between tissue parameters and laser parameters in the outcome of the removal of dental hard tissue is discussed in detail.

Electrospraying of polymer solutions: Study of formulation and process parameters.

PubMed

Smeets, Annelies; Clasen, Christian; Van den Mooter, Guy

2017-10-01

Over the past decade, electrospraying has proven to be a promising method for the preparation of amorphous solid dispersions, an established formulation strategy to improve the oral bioavailability of poorly soluble drug compounds. Due to the lack of fundamental knowledge concerning adequate single nozzle electrospraying conditions, a trial-and-error approach is currently the only option. The objective of this paper is to study/investigate the influence of the different formulation and process parameters, as well as their interplay, on the formation of a stable cone-jet mode as a prerequisite for a reproducible production of monodisperse micro- and nanoparticles. To this purpose, different polymers commonly used in the formulation of solid dispersions were electrosprayed to map out the workable parameter ranges of the process. The experiments evaluate the importance of the experimental parameters as flow rate, electric potential difference and the distance between the tip of the nozzle and collector. Based on this, the type of solvent and the concentration of the polymer solutions, along with their viscosity and conductivity, were identified as determinative formulation parameters. This information is of utmost importance to rationally design further electrospraying methods for the preparation of amorphous solid dispersions. Copyright © 2017 Elsevier B.V. All rights reserved.

Experimental Research on Selective Laser Melting AlSi10Mg Alloys: Process, Densification and Performance

NASA Astrophysics Data System (ADS)

Chen, Zhen; Wei, Zhengying; Wei, Pei; Chen, Shenggui; Lu, Bingheng; Du, Jun; Li, Junfeng; Zhang, Shuzhe

2017-12-01

In this work, a set of experiments was designed to investigate the effect of process parameters on the relative density of the AlSi10Mg parts manufactured by SLM. The influence of laser scan speed v, laser power P and hatch space H, which were considered as the dominant parameters, on the powder melting and densification behavior was also studied experimentally. In addition, the laser energy density was introduced to evaluate the combined effect of the above dominant parameters, so as to control the SLM process integrally. As a result, a high relative density (> 97%) was obtained by SLM at an optimized laser energy density of 3.5-5.5 J/mm2. Moreover, a parameter-densification map was established to visually select the optimum process parameters for the SLM-processed AlSi10Mg parts with elevated density and required mechanical properties. The results provide an important experimental guidance for obtaining AlSi10Mg components with full density and gradient functional porosity by SLM.

Polishing tool and the resulting TIF for three variable machine parameters as input for the removal simulation

NASA Astrophysics Data System (ADS)

Schneider, Robert; Haberl, Alexander; Rascher, Rolf

2017-06-01

The trend in the optic industry shows, that it is increasingly important to be able to manufacture complex lens geometries on a high level of precision. From a certain limit on the required shape accuracy of optical workpieces, the processing is changed from the two-dimensional to point-shaped processing. It is very important that the process is as stable as possible during the in point-shaped processing. To ensure stability, usually only one process parameter is varied during processing. It is common that this parameter is the feed rate, which corresponds to the dwell time. In the research project ArenA-FOi (Application-oriented analysis of resource-saving and energy-efficient design of industrial facilities for the optical industry), a touching procedure is used in the point-attack, and in this case a close look is made as to whether a change of several process parameters is meaningful during a processing. The ADAPT tool in size R20 from Satisloh AG is used, which is also available for purchase. The behavior of the tool is tested under constant conditions in the MCP 250 CNC by OptoTech GmbH. A series of experiments should enable the TIF (tool influence function) to be determined using three variable parameters. Furthermore, the maximum error frequency that can be processed is calculated as an example for one parameter set and serves as an outlook for further investigations. The test results serve as the basic for the later removal simulation, which must be able to deal with a variable TIF. This topic has already been successfully implemented in another research project of the Institute for Precision Manufacturing and High-Frequency Technology (IPH) and thus this algorithm can be used. The next step is the useful implementation of the collected knowledge. The TIF must be selected on the basis of the measured data. It is important to know the error frequencies to select the optimal TIF. Thus, it is possible to compare the simulated results with real measurement data and to carry out a revision. From this point onwards, it is possible to evaluate the potential of this approach, and in the ideal case it will be further researched and later found in the production.

Economic design of control charts considering process shift distributions

NASA Astrophysics Data System (ADS)

Vommi, Vijayababu; Kasarapu, Rukmini V.

2014-09-01

Process shift is an important input parameter in the economic design of control charts. Earlier control chart designs considered constant shifts to occur in the mean of the process for a given assignable cause. This assumption has been criticized by many researchers since it may not be realistic to produce a constant shift whenever an assignable cause occurs. To overcome this difficulty, in the present work, a distribution for the shift parameter has been considered instead of a single value for a given assignable cause. Duncan's economic design model for chart has been extended to incorporate the distribution for the process shift parameter. It is proposed to minimize total expected loss-cost to obtain the control chart parameters. Further, three types of process shifts namely, positively skewed, uniform and negatively skewed distributions are considered and the situations where it is appropriate to use the suggested methodology are recommended.

Application of identified sensitive physical parameters in reducing the uncertainty of numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2016-04-01

An important source of uncertainty, which then causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. There are many physical parameters in numerical models in the atmospheric and oceanic sciences, and it would cost a great deal to reduce uncertainties in all physical parameters. Therefore, finding a subset of these parameters, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach. The results imply that nonlinear interactions among parameters play a key role in the uncertainty of numerical simulations in arid and semi-arid regions of China compared to those in northern, northeastern and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

Impact Of The Material Variability On The Stamping Process: Numerical And Analytical Analysis

NASA Astrophysics Data System (ADS)

Ledoux, Yann; Sergent, Alain; Arrieux, Robert

2007-05-01

The finite element simulation is a very useful tool in the deep drawing industry. It is used more particularly for the development and the validation of new stamping tools. It allows to decrease cost and time for the tooling design and set up. But one of the most important difficulties to have a good agreement between the simulation and the real process comes from the definition of the numerical conditions (mesh, punch travel speed, limit conditions,…) and the parameters which model the material behavior. Indeed, in press shop, when the sheet set changes, often a variation of the formed part geometry is observed according to the variability of the material properties between these different sets. This last parameter represents probably one of the main source of process deviation when the process is set up. That's why it is important to study the influence of material data variation on the geometry of a classical stamped part. The chosen geometry is an omega shaped part because of its simplicity and it is representative one in the automotive industry (car body reinforcement). Moreover, it shows important springback deviations. An isotropic behaviour law is assumed. The impact of the statistical deviation of the three law coefficients characterizing the material and the friction coefficient around their nominal values is tested. A Gaussian distribution is supposed and their impact on the geometry variation is studied by FE simulation. An other approach is envisaged consisting in modeling the process variability by a mathematical model and then, in function of the input parameters variability, it is proposed to define an analytical model which leads to find the part geometry variability around the nominal shape. These two approaches allow to predict the process capability as a function of the material parameter variability.

Mining manufacturing data for discovery of high productivity process characteristics.

PubMed

Charaniya, Salim; Le, Huong; Rangwala, Huzefa; Mills, Keri; Johnson, Kevin; Karypis, George; Hu, Wei-Shou

2010-06-01

Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 'trains' comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses. 2010 Elsevier B.V. All rights reserved.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis

NASA Astrophysics Data System (ADS)

Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.

2017-03-01

Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

2015-12-01

Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes or both to determine the full range of sensitivity of Earth system modeling to land-surface parameters. This can facilitate sampling strategies in measurement campaigns targeted at reduction of climate modeling uncertainties and can also provide guidance on land parameter calibration for simulation optimization.

UCMS - A new signal parameter measurement system using digital signal processing techniques. [User Constraint Measurement System

NASA Technical Reports Server (NTRS)

Choi, H. J.; Su, Y. T.

1986-01-01

The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

Assessment of Process Capability: the case of Soft Drinks Processing Unit

NASA Astrophysics Data System (ADS)

Sri Yogi, Kottala

2018-03-01

The process capability studies have significant impact in investigating process variation which is important in achieving product quality characteristics. Its indices are to measure the inherent variability of a process and thus to improve the process performance radically. The main objective of this paper is to understand capability of the process being produced within specification of the soft drinks processing unit, a premier brands being marketed in India. A few selected critical parameters in soft drinks processing: concentration of gas volume, concentration of brix, torque of crock has been considered for this study. Assessed some relevant statistical parameters: short term capability, long term capability as a process capability indices perspective. For assessment we have used real time data of soft drinks bottling company which is located in state of Chhattisgarh, India. As our research output suggested reasons for variations in the process which is validated using ANOVA and also predicted Taguchi cost function, assessed also predicted waste monetarily this shall be used by organization for improving process parameters. This research work has substantially benefitted the organization in understanding the various variations of selected critical parameters for achieving zero rejection.

Investigation on influence of Wurster coating process parameters for the development of delayed release minitablets of Naproxen.

PubMed

Shah, Neha; Mehta, Tejal; Aware, Rahul; Shetty, Vasant

2017-12-01

The present work aims at studying process parameters affecting coating of minitablets (3 mm in diameter) through Wurster coating process. Minitablets of Naproxen with high drug loading were manufactured using 3 mm multi-tip punches. The release profile of core pellets (published) and minitablets was compared with that of marketed formulation. The core formulation of minitablets was found to show similarity in dissolution profile with marketed formulation and hence was further carried forward for functional coating over it. Wurster processing was implemented to pursue functional coating over core formulation. Different process parameters were screened and control strategy was applied for factors significantly affecting the process. Modified Plackett Burman Design was applied for studying important factors. Based on the significant factors and minimum level of coating required for functionalization, optimized process was executed. Final coated batch was evaluated for coating thickness, surface morphology, and drug release study.

Probabilistic modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less

The importance of diverse data types to calibrate a watershed model of the Trout Lake Basin, Northern Wisconsin, USA

USGS Publications Warehouse

Hunt, R.J.; Feinstein, D.T.; Pint, C.D.; Anderson, M.P.

2006-01-01

As part of the USGS Water, Energy, and Biogeochemical Budgets project and the NSF Long-Term Ecological Research work, a parameter estimation code was used to calibrate a deterministic groundwater flow model of the Trout Lake Basin in northern Wisconsin. Observations included traditional calibration targets (head, lake stage, and baseflow observations) as well as unconventional targets such as groundwater flows to and from lakes, depth of a lake water plume, and time of travel. The unconventional data types were important for parameter estimation convergence and allowed the development of a more detailed parameterization capable of resolving model objectives with well-constrained parameter values. Independent estimates of groundwater inflow to lakes were most important for constraining lakebed leakance and the depth of the lake water plume was important for determining hydraulic conductivity and conceptual aquifer layering. The most important target overall, however, was a conventional regional baseflow target that led to correct distribution of flow between sub-basins and the regional system during model calibration. The use of an automated parameter estimation code: (1) facilitated the calibration process by providing a quantitative assessment of the model's ability to match disparate observed data types; and (2) allowed assessment of the influence of observed targets on the calibration process. The model calibration required the use of a 'universal' parameter estimation code in order to include all types of observations in the objective function. The methods described in this paper help address issues of watershed complexity and non-uniqueness common to deterministic watershed models. ?? 2005 Elsevier B.V. All rights reserved.

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

Quantifying the sensitivity of feedstock properties and process conditions on hydrochar yield, carbon content, and energy content.

PubMed

Li, Liang; Wang, Yiying; Xu, Jiting; Flora, Joseph R V; Hoque, Shamia; Berge, Nicole D

2018-08-01

Hydrothermal carbonization (HTC) is a wet, low temperature thermal conversion process that continues to gain attention for the generation of hydrochar. The importance of specific process conditions and feedstock properties on hydrochar characteristics is not well understood. To evaluate this, linear and non-linear models were developed to describe hydrochar characteristics based on data collected from HTC-related literature. A Sobol analysis was subsequently conducted to identify parameters that most influence hydrochar characteristics. Results from this analysis indicate that for each investigated hydrochar property, the model fit and predictive capability associated with the random forest models is superior to both the linear and regression tree models. Based on results from the Sobol analysis, the feedstock properties and process conditions most influential on hydrochar yield, carbon content, and energy content were identified. In addition, a variational process parameter sensitivity analysis was conducted to determine how feedstock property importance changes with process conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Investigation about the Chrome Steel Wire Arc Spray Process and the Resulting Coating Properties

NASA Astrophysics Data System (ADS)

Wilden, J.; Bergmann, J. P.; Jahn, S.; Knapp, S.; van Rodijnen, F.; Fischer, G.

2007-12-01

Nowadays, wire-arc spraying of chromium steel has gained an important market share for corrosion and wear protection applications. However, detailed studies are the basis for further process optimization. In order to optimize the process parameters and to evaluate the effects of the spray parameters DoE-based experiments had been carried out with high-speed camera shoots. In this article, the effects of spray current, voltage, and atomizing gas pressure on the particle jet properties, mean particle velocity and mean particle temperature and plume width on X46Cr13 wire are presented using an online process monitoring device. Moreover, the properties of the coatings concerning the morphology, composition and phase formation were subject of the investigations using SEM, EDX, and XRD-analysis. These deep investigations allow a defined verification of the influence of process parameters on spray plume and coating properties and are the basis for further process optimization.

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

Effects of Processing Parameters on the Forming Quality of C-Shaped Thermosetting Composite Laminates in Hot Diaphragm Forming Process

NASA Astrophysics Data System (ADS)

Bian, X. X.; Gu, Y. Z.; Sun, J.; Li, M.; Liu, W. P.; Zhang, Z. G.

2013-10-01

In this study, the effects of processing temperature and vacuum applying rate on the forming quality of C-shaped carbon fiber reinforced epoxy resin matrix composite laminates during hot diaphragm forming process were investigated. C-shaped prepreg preforms were produced using a home-made hot diaphragm forming equipment. The thickness variations of the preforms and the manufacturing defects after diaphragm forming process, including fiber wrinkling and voids, were evaluated to understand the forming mechanism. Furthermore, both interlaminar slipping friction and compaction behavior of the prepreg stacks were experimentally analyzed for showing the importance of the processing parameters. In addition, autoclave processing was used to cure the C-shaped preforms to investigate the changes of the defects before and after cure process. The results show that the C-shaped prepreg preforms with good forming quality can be achieved through increasing processing temperature and reducing vacuum applying rate, which obviously promote prepreg interlaminar slipping process. The process temperature and forming rate in hot diaphragm forming process strongly influence prepreg interply frictional force, and the maximum interlaminar frictional force can be taken as a key parameter for processing parameter optimization. Autoclave process is effective in eliminating voids in the preforms and can alleviate fiber wrinkles to a certain extent.

A Comparative Study on Ni-Based Coatings Prepared by HVAF, HVOF, and APS Methods for Corrosion Protection Applications

NASA Astrophysics Data System (ADS)

Sadeghimeresht, E.; Markocsan, N.; Nylén, P.

2016-12-01

Selection of the thermal spray process is the most important step toward a proper coating solution for a given application as important coating characteristics such as adhesion and microstructure are highly dependent on it. In the present work, a process-microstructure-properties-performance correlation study was performed in order to figure out the main characteristics and corrosion performance of the coatings produced by different thermal spray techniques such as high-velocity air fuel (HVAF), high-velocity oxy fuel (HVOF), and atmospheric plasma spraying (APS). Previously optimized HVOF and APS process parameters were used to deposit Ni, NiCr, and NiAl coatings and compare with HVAF-sprayed coatings with randomly selected process parameters. As the HVAF process presented the best coating characteristics and corrosion behavior, few process parameters such as feed rate and standoff distance (SoD) were investigated to systematically optimize the HVAF coatings in terms of low porosity and high corrosion resistance. The Ni and NiAl coatings with lower porosity and better corrosion behavior were obtained at an average SoD of 300 mm and feed rate of 150 g/min. The NiCr coating sprayed at a SoD of 250 mm and feed rate of 75 g/min showed the highest corrosion resistance among all investigated samples.

Flow Tube Studies of Gas Phase Chemical Processes of Atmospheric Importance

NASA Technical Reports Server (NTRS)

Molina, Mario J.

1997-01-01

The objective of this project is to conduct measurements of elementary reaction rate constants and photochemistry parameters for processes of importance in the atmosphere. These measurements are being carried out under temperature and pressure conditions covering those applicable to the stratosphere and upper troposphere, using the chemical ionization mass spectrometry turbulent flow technique developed in our laboratory.

Glycerin Reformation in High Temperature and Pressure Water

DTIC Science & Technology

2012-01-01

73 3.2.5. Process Sampling………………………………..…….……..75 3.3. PROCESS SAFETY………………………………………..…..........76 3.4. ANALYTICAL EQUIPMENT...compared to micro-reactors. This is important for new process development as well as scale-up of the process system. These two insights, the most...important parameters and the feasibility of scale-up, offer opportunities to maximize the process and scale-up further to industrial applications 1.2

A Knowledge Database on Thermal Control in Manufacturing Processes

NASA Astrophysics Data System (ADS)

Hirasawa, Shigeki; Satoh, Isao

A prototype version of a knowledge database on thermal control in manufacturing processes, specifically, molding, semiconductor manufacturing, and micro-scale manufacturing has been developed. The knowledge database has search functions for technical data, evaluated benchmark data, academic papers, and patents. The database also displays trends and future roadmaps for research topics. It has quick-calculation functions for basic design. This paper summarizes present research topics and future research on thermal control in manufacturing engineering to collate the information to the knowledge database. In the molding process, the initial mold and melt temperatures are very important parameters. In addition, thermal control is related to many semiconductor processes, and the main parameter is temperature variation in wafers. Accurate in-situ temperature measurment of wafers is important. And many technologies are being developed to manufacture micro-structures. Accordingly, the knowledge database will help further advance these technologies.

Effect of Geometric Parameters on Formability and Strain Path During Tube Hydrforming Process

NASA Astrophysics Data System (ADS)

Omar, A.; Harisankar, K. R.; Tewari, Asim; Narasimhan, K.

2016-08-01

Forming limit diagram (FLD) is an important tool to measure the material's formability for metal forming processes. In order to successfully manufacture a component through tube hydroforming process it is very important to know the effect of material properties, process and geometrical parameters on the outcome of finished product. This can be obtained by running a finite element code which not only saves time and money but also gives a result with considerable accuracy. Therefore, in this paper the mutual effect of diameter as well as thickness has been studied. Firstly the finite element based prediction is carried out to assess the formability of seamless and welded tubes with varying thickness. Later on, effect of varying diameter and thickness on strain path is predicted using statistical based regression analysis. Finally, the mutual effect of varying material property alongwith varying thickness and diameter on constraint factor is studied.

Elements of an algorithm for optimizing a parameter-structural neural network

NASA Astrophysics Data System (ADS)

Mrówczyńska, Maria

2016-06-01

The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH), which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.

Laser-Ultrasonic Measurement of Elastic Properties of Anodized Aluminum Coatings

NASA Astrophysics Data System (ADS)

Singer, F.

Anodized aluminum oxide plays a great role in many industrial applications, e.g. in order to achieve greater wear resistance. Since the hardness of the anodized films strongly depends on its processing parameters, it is important to characterize the influence of the processing parameters on the film properties. In this work the elastic material parameters of anodized aluminum were investigated using a laser-based ultrasound system. The anodized films were characterized analyzing the dispersion of Rayleigh waves with a one-layer model. It was shown that anodizing time and temperature strongly influence Rayleigh wave propagation.

Typecasting catchments: Classification, directionality, and the pursuit of universality

NASA Astrophysics Data System (ADS)

Smith, Tyler; Marshall, Lucy; McGlynn, Brian

2018-02-01

Catchment classification poses a significant challenge to hydrology and hydrologic modeling, restricting widespread transfer of knowledge from well-studied sites. The identification of important physical, climatological, or hydrologic attributes (to varying degrees depending on application/data availability) has traditionally been the focus for catchment classification. Classification approaches are regularly assessed with regard to their ability to provide suitable hydrologic predictions - commonly by transferring fitted hydrologic parameters at a data-rich catchment to a data-poor catchment deemed similar by the classification. While such approaches to hydrology's grand challenges are intuitive, they often ignore the most uncertain aspect of the process - the model itself. We explore catchment classification and parameter transferability and the concept of universal donor/acceptor catchments. We identify the implications of the assumption that the transfer of parameters between "similar" catchments is reciprocal (i.e., non-directional). These concepts are considered through three case studies situated across multiple gradients that include model complexity, process description, and site characteristics. Case study results highlight that some catchments are more successfully used as donor catchments and others are better suited as acceptor catchments. These results were observed for both black-box and process consistent hydrologic models, as well as for differing levels of catchment similarity. Therefore, we suggest that similarity does not adequately satisfy the underlying assumptions being made in parameter regionalization approaches regardless of model appropriateness. Furthermore, we suggest that the directionality of parameter transfer is an important factor in determining the success of parameter regionalization approaches.

Thermo-Mechanical Calculations of Hybrid Rotary Friction Welding at Equal Diameter Copper Bars and Effects of Essential Parameters on Dependent Special Variables

NASA Astrophysics Data System (ADS)

Parsa, M. H.; Davari, H.; Hadian, A. M.; Ahmadabadi, M. Nili

2007-05-01

Hybrid Rotary Friction Welding is a modified type of common rotary friction welding processes. In this welding method parameters such as pressure, angular velocity and time of welding control temperature, stress, strain and their variations. These dependent factors play an important rule in defining optimum process parameters combinations in order to improve the design and manufacturing of welding machines and quality of welded parts. Thermo-mechanical simulation of friction welding has been carried out and it has been shown that, simulation is an important tool for prediction of generated heat and strain at the weld interface and can be used for prediction of microstructure and evaluation of quality of welds. For simulation of Hybrid Rotary Friction Welding, a commercial finite element program has been used and the effects of pressure and rotary velocity of rotary part on temperature and strain variations have been investigated.

Green-ampt infiltration parameters in riparian buffers

Treesearch

L.M. Stahr; D.E. Eisenhauer; M.J. Helmers; Mike G. Dosskey; T.G. Franti

2004-01-01

Riparian buffers can improve surface water quality by filtering contaminants from runoff before they enter streams. Infiltration is an important process in riparian buffers. Computer models are often used to assess the performance of riparian buffers. Accurate prediction of infiltration by these models is dependent upon accurate estimates of infiltration parameters....

The effect of nozzle-exit-channel shape on resultant fiber diameter in melt-electrospinning

NASA Astrophysics Data System (ADS)

Esmaeilirad, Ahmad; Ko, Junghyuk; Rukosuyev, Maxym V.; Lee, Jason K.; Lee, Patrick C.; Jun, Martin B. G.

2017-01-01

In recent decades, electrospinning using a molten poly (ε-caprolactone) resin has gained attention for creating fibrous tissue scaffolds. The topography and diameter control of such electrospun microfibers is an important issue for their different applications in tissue engineering. Charge density, initial nozzle-exit-channel cross-sectional area, nozzle to collector distance, viscosity, and processing temperature are the most important input parameters that affect the final electrospun fiber diameters. In this paper we will show that the effect of nozzle-exit-channel shape is as important as the other effective parameters in a resultant fiber diameter. However, to the best of our knowledge, the effect of nozzle-exit-channel shapes on a resultant fiber diameter have not been studied before. Comparing rectangular and circular nozzles with almost the same exit-channel cross-sectional areas in a similar processing condition showed that using a rectangular nozzle resulted in decreasing final fiber diameter up to 50%. Furthermore, the effect of processing temperature on the final fiber topography was investigated.

Training Guide for Severe Weather Forecasters

DTIC Science & Technology

1979-11-01

that worked very well for the example forecast is used to show the importance of parameter intensities and the actual thought processes that go into the...simplify the explanation of the complete level analysis. This entire process will be repeated for the 700 mb and 500 mb levels. Details in Figures 1 through...parameters of moderate to strong intensity must occur, in the same place at the same time. A description of what constitutes a weak, moderate, or strong

Optical spectral signatures of liquids by means of fiber optic technology for product and quality parameter identification

NASA Astrophysics Data System (ADS)

Mignani, A. G.; Ciaccheri, L.; Mencaglia, A. A.; Diaz-Herrera, N.; Garcia-Allende, P. B.; Ottevaere, H.; Thienpont, H.; Attilio, C.; Cimato, A.; Francalanci, S.; Paccagnini, A.; Pavone, F. S.

2009-01-01

Absorption spectroscopy in the wide 200-1700 nm spectral range is carried out by means of optical fiber instrumentation to achieve a digital mapping of liquids for the prediction of important quality parameters. Extra virgin olive oils from Italy and lubricant oils from turbines with different degrees of degradation were considered as "case studies". The spectral data were processed by means of multivariate analysis so as to obtain a correlation to quality parameters. In practice, the wide range absorption spectra were considered as an optical signature of the liquids from which to extract product quality information. The optical signatures of extra virgin olive oils were used to predict the content of the most important fatty acids. The optical signatures of lubricant oils were used to predict the concentration of the most important parameters for indicating the oil's degree of degradation, such as TAN, JOAP anti-wear index, and water content.

iMOSFLM: a new graphical interface for diffraction-image processing with MOSFLM

PubMed Central

Battye, T. Geoff G.; Kontogiannis, Luke; Johnson, Owen; Powell, Harold R.; Leslie, Andrew G. W.

2011-01-01

iMOSFLM is a graphical user interface to the diffraction data-integration program MOSFLM. It is designed to simplify data processing by dividing the process into a series of steps, which are normally carried out sequentially. Each step has its own display pane, allowing control over parameters that influence that step and providing graphical feedback to the user. Suitable values for integration parameters are set automatically, but additional menus provide a detailed level of control for experienced users. The image display and the interfaces to the different tasks (indexing, strategy calculation, cell refinement, integration and history) are described. The most important parameters for each step and the best way of assessing success or failure are discussed. PMID:21460445

Comparative Assessment of Cutting Inserts and Optimization during Hard Turning: Taguchi-Based Grey Relational Analysis

NASA Astrophysics Data System (ADS)

Venkata Subbaiah, K.; Raju, Ch.; Suresh, Ch.

2017-08-01

The present study aims to compare the conventional cutting inserts with wiper cutting inserts during the hard turning of AISI 4340 steel at different workpiece hardness. Type of insert, hardness, cutting speed, feed, and depth of cut are taken as process parameters. Taguchi’s L18 orthogonal array was used to conduct the experimental tests. Parametric analysis carried in order to know the influence of each process parameter on the three important Surface Roughness Characteristics (Ra, Rz, and Rt) and Material Removal Rate. Taguchi based Grey Relational Analysis (GRA) used to optimize the process parameters for individual response and multi-response outputs. Additionally, the analysis of variance (ANOVA) is also applied to identify the most significant factor.

Framework for Uncertainty Assessment - Hanford Site-Wide Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Bergeron, M. P.; Cole, C. R.; Murray, C. J.; Thorne, P. D.; Wurstner, S. K.

2002-05-01

Pacific Northwest National Laboratory is in the process of development and implementation of an uncertainty estimation methodology for use in future site assessments that addresses parameter uncertainty as well as uncertainties related to the groundwater conceptual model. The long-term goals of the effort are development and implementation of an uncertainty estimation methodology for use in future assessments and analyses being made with the Hanford site-wide groundwater model. The basic approach in the framework developed for uncertainty assessment consists of: 1) Alternate conceptual model (ACM) identification to identify and document the major features and assumptions of each conceptual model. The process must also include a periodic review of the existing and proposed new conceptual models as data or understanding become available. 2) ACM development of each identified conceptual model through inverse modeling with historical site data. 3) ACM evaluation to identify which of conceptual models are plausible and should be included in any subsequent uncertainty assessments. 4) ACM uncertainty assessments will only be carried out for those ACMs determined to be plausible through comparison with historical observations and model structure identification measures. The parameter uncertainty assessment process generally involves: a) Model Complexity Optimization - to identify the important or relevant parameters for the uncertainty analysis; b) Characterization of Parameter Uncertainty - to develop the pdfs for the important uncertain parameters including identification of any correlations among parameters; c) Propagation of Uncertainty - to propagate parameter uncertainties (e.g., by first order second moment methods if applicable or by a Monte Carlo approach) through the model to determine the uncertainty in the model predictions of interest. 5)Estimation of combined ACM and scenario uncertainty by a double sum with each component of the inner sum (an individual CCDF) representing parameter uncertainty associated with a particular scenario and ACM and the outer sum enumerating the various plausible ACM and scenario combinations in order to represent the combined estimate of uncertainty (a family of CCDFs). A final important part of the framework includes identification, enumeration, and documentation of all the assumptions, which include those made during conceptual model development, required by the mathematical model, required by the numerical model, made during the spatial and temporal descretization process, needed to assign the statistical model and associated parameters that describe the uncertainty in the relevant input parameters, and finally those assumptions required by the propagation method. Pacific Northwest National Laboratory is operated for the U.S. Department of Energy under Contract DE-AC06-76RL01830.

Identification of critical process variables affecting particle size following precipitation using a supercritical fluid.

PubMed

Sacha, Gregory A; Schmitt, William J; Nail, Steven L

2006-01-01

The critical processing parameters affecting average particle size, particle size distribution, yield, and level of residual carrier solvent using the supercritical anti-solvent method (SAS) were identified. Carbon dioxide was used as the supercritical fluid. Methylprednisolone acetate was used as the model solute in tetrahydrofuran. Parameters examined included pressure of the supercritical fluid, agitation rate, feed solution flow rate, impeller diameter, and nozzle design. Pressure was identified as the most important process parameter affecting average particle size, either through the effect of pressure on dispersion of the feed solution into the precipitation vessel or through the effect of pressure on solubility of drug in the CO2/organic solvent mixture. Agitation rate, impeller diameter, feed solution flow rate, and nozzle design had significant effects on particle size, which suggests that dispersion of the feed solution is important. Crimped HPLC tubing was the most effective method of introducing feed solution into the precipitation vessel, largely because it resulted in the least amount of clogging during the precipitation. Yields of 82% or greater were consistently produced and were not affected by the processing variables. Similarly, the level of residual solvent was independent of the processing variables and was present at 0.0002% wt/wt THF or less.

Setting priorities in health care organizations: criteria, processes, and parameters of success.

PubMed

Gibson, Jennifer L; Martin, Douglas K; Singer, Peter A

2004-09-08

Hospitals and regional health authorities must set priorities in the face of resource constraints. Decision-makers seek practical ways to set priorities fairly in strategic planning, but find limited guidance from the literature. Very little has been reported from the perspective of Board members and senior managers about what criteria, processes and parameters of success they would use to set priorities fairly. We facilitated workshops for board members and senior leadership at three health care organizations to assist them in developing a strategy for fair priority setting. Workshop participants identified 8 priority setting criteria, 10 key priority setting process elements, and 6 parameters of success that they would use to set priorities in their organizations. Decision-makers in other organizations can draw lessons from these findings to enhance the fairness of their priority setting decision-making. Lessons learned in three workshops fill an important gap in the literature about what criteria, processes, and parameters of success Board members and senior managers would use to set priorities fairly.

MontePython 3: Parameter inference code for cosmology

NASA Astrophysics Data System (ADS)

Brinckmann, Thejs; Lesgourgues, Julien; Audren, Benjamin; Benabed, Karim; Prunet, Simon

2018-05-01

MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

Diamond Deposition and Defect Chemistry Studied via Solid State NMR

DTIC Science & Technology

1994-06-30

system can be found elsewhere (121. The flame characteristics depend on a number of parameters . The flame conditions depend on (a) equivalence ratio...b) pressure, (c) cold gas velocity, and (d) diluent. The effect of the various parameters are described briefly. This quantity describes the carbon...important parameter that must be controlled carefully. Many chemical processes in flames, including those in which collision activation or stabilization

Laser Photochemistry.

DTIC Science & Technology

1981-07-01

continuum and is the important parameter for determining the dissociation yield (Grant et al., 1978). The phenomenon of infrared MPE and MPD seems well under...incoherent absorption processes in MPE and MPD? What is the magnitude of the absorption cross section and how does it change with molecular parameters ...iv) What is the dynamics of the dissociation event and what are the parameters that determine the rate of unimolecular decom- position? (v) How can

Color separation in forensic image processing using interactive differential evolution.

PubMed

Mushtaq, Harris; Rahnamayan, Shahryar; Siddiqi, Areeb

2015-01-01

Color separation is an image processing technique that has often been used in forensic applications to differentiate among variant colors and to remove unwanted image interference. This process can reveal important information such as covered text or fingerprints in forensic investigation procedures. However, several limitations prevent users from selecting the appropriate parameters pertaining to the desired and undesired colors. This study proposes the hybridization of an interactive differential evolution (IDE) and a color separation technique that no longer requires users to guess required control parameters. The IDE algorithm optimizes these parameters in an interactive manner by utilizing human visual judgment to uncover desired objects. A comprehensive experimental verification has been conducted on various sample test images, including heavily obscured texts, texts with subtle color variations, and fingerprint smudges. The advantage of IDE is apparent as it effectively optimizes the color separation parameters at a level indiscernible to the naked eyes. © 2014 American Academy of Forensic Sciences.

Continuous melt granulation: Influence of process and formulation parameters upon granule and tablet properties.

PubMed

Monteyne, Tinne; Vancoillie, Jochem; Remon, Jean-Paul; Vervaet, Chris; De Beer, Thomas

2016-10-01

The pharmaceutical industry has a growing interest in alternative manufacturing models allowing automation and continuous production in order to improve process efficiency and reduce costs. Implementing a switch from batch to continuous processing requires fundamental process understanding and the implementation of quality-by-design (QbD) principles. The aim of this study was to examine the relationship between formulation-parameters (type binder, binder concentration, drug-binder miscibility), process-parameters (screw speed, powder feed rate and granulation temperature), granule properties (size, size distribution, shape, friability, true density, flowability) and tablet properties (tensile strength, friability, dissolution rate) of four different drug-binder formulations using Design of experiments (DOE). Two binders (polyethylene glycol (PEG) and Soluplus®) with a different solid state, semi-crystalline vs amorphous respectively, were combined with two model-drugs, metoprolol tartrate (MPT) and caffeine anhydrous (CAF), both having a contrasting miscibility with the binders. This research revealed that the granule properties of miscible drug-binder systems depended on the powder feed rate and barrel filling degree of the granulator whereas the granule properties of immiscible systems were mainly influenced by binder concentration. Using an amorphous binder, the tablet tensile strength depended on the granule size. In contrast, granule friability was more important for tablet quality using a brittle binder. However, this was not the case for caffeine-containing blends, since these phenomena were dominated by the enhanced compression properties of caffeine Form I, which was formed during granulation. Hence, it is important to gain knowledge about formulation behavior during processing since this influences the effect of process parameters onto the granule and tablet properties. Copyright © 2016 Elsevier B.V. All rights reserved.

Experiments for practical education in process parameter optimization for selective laser sintering to increase workpiece quality

NASA Astrophysics Data System (ADS)

Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas

2016-04-01

Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Optimisation of warpage on plastic injection moulding part using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Miza, A. T. N. A.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Rashidi, M. M.

2017-09-01

The warpage is often encountered which occur during injection moulding process of thin shell part depending the process condition. The statistical design of experiment method which are Integrating Finite Element (FE) Analysis, moldflow analysis and response surface methodology (RSM) are the stage of few ways in minimize the warpage values of x,y and z on thin shell plastic parts that were investigated. A battery cover of a remote controller is one of the thin shell plastic part that produced by using injection moulding process. The optimum process condition parameter were determined as to achieve the minimum warpage from being occur. Packing pressure, Cooling time, Melt temperature and Mould temperature are 4 parameters that considered in this study. A two full factorial experimental design was conducted in Design Expert of RSM analysis as to combine all these parameters study. FE analysis result gain from analysis of variance (ANOVA) method was the one of the important process parameters influenced warpage. By using RSM, a predictive response surface model for warpage data will be shown.

Warpage minimization on wheel caster by optimizing process parameters using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

In injection moulding process, it is important to keep the productivity increase constantly with least of waste produced such as warpage defect. Thus, this study is concerning on minimizing warpage defect on wheel caster part. Apart from eliminating product wastes, this project also giving out best optimization techniques using response surface methodology. This research studied on five parameters A-packing pressure, B-packing time, C-mold temperature, D-melting temperature and E-cooling time. The optimization showed that packing pressure is the most significant parameter. Warpage have been improved 42.64% from 0.6524 mm to 0.3742mm.

Bioreactor process parameter screening utilizing a Plackett-Burman design for a model monoclonal antibody.

PubMed

Agarabi, Cyrus D; Schiel, John E; Lute, Scott C; Chavez, Brittany K; Boyne, Michael T; Brorson, Kurt A; Khan, Mansoora; Read, Erik K

2015-06-01

Consistent high-quality antibody yield is a key goal for cell culture bioprocessing. This endpoint is typically achieved in commercial settings through product and process engineering of bioreactor parameters during development. When the process is complex and not optimized, small changes in composition and control may yield a finished product of less desirable quality. Therefore, changes proposed to currently validated processes usually require justification and are reported to the US FDA for approval. Recently, design-of-experiments-based approaches have been explored to rapidly and efficiently achieve this goal of optimized yield with a better understanding of product and process variables that affect a product's critical quality attributes. Here, we present a laboratory-scale model culture where we apply a Plackett-Burman screening design to parallel cultures to study the main effects of 11 process variables. This exercise allowed us to determine the relative importance of these variables and identify the most important factors to be further optimized in order to control both desirable and undesirable glycan profiles. We found engineering changes relating to culture temperature and nonessential amino acid supplementation significantly impacted glycan profiles associated with fucosylation, β-galactosylation, and sialylation. All of these are important for monoclonal antibody product quality. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Brief Report: Coherent Motion Processing in Autism: Is Dot Lifetime an Important Parameter?

ERIC Educational Resources Information Center

Manning, Catherine; Charman, Tony; Pellicano, Elizabeth

2015-01-01

Contrasting reports of "reduced" and "intact" sensitivity to coherent motion in autistic individuals may be attributable to stimulus parameters. Here, we investigated whether dot lifetime contributes to elevated thresholds in children with autism. We presented a standard motion coherence task to 31 children with autism and 31…

An Attempt of Formalizing the Selection Parameters for Settlements Generalization in Small-Scales

NASA Astrophysics Data System (ADS)

Karsznia, Izabela

2014-12-01

The paper covers one of the most important problems concerning context-sensitive settlement selection for the purpose of the small-scale maps. So far, no formal parameters for small-scale settlements generalization have been specified, hence the problem seems to be an important and innovative challenge. It is also crucial from the practical point of view as it is necessary to develop appropriate generalization algorithms for the purpose of the General Geographic Objects Database generalization which is the essential Spatial Data Infrastructure component in Poland. The author proposes and verifies quantitative generalization parameters for the purpose of the settlement selection process in small-scale maps. The selection of settlements was carried out in two research areas - in Lower Silesia and Łódź Province. Based on the conducted analysis appropriate contextual-sensitive settlements selection parameters have been defined. Particular effort has been made to develop a methodology of quantitative settlements selection which would be useful in the automation processes and that would make it possible to keep specifics of generalized objects unchanged.

PARAMETERS OF TREATED STAINLESS STEEL SURFACES IMPORTANT FOR RESISTANCE TO BACTERIAL CONTAMINATION

EPA Science Inventory

Use of materials that are resistant to bacterial contamination could enhance food safety during processing. Common finishing treatments of stainless steel surfaces used for components of poultry processing equipment were tested for resistance to bacterial attachment. Surface char...

Process development for robust removal of aggregates using cation exchange chromatography in monoclonal antibody purification with implementation of quality by design.

PubMed

Xu, Zhihao; Li, Jason; Zhou, Joe X

2012-01-01

Aggregate removal is one of the most important aspects in monoclonal antibody (mAb) purification. Cation-exchange chromatography (CEX), a widely used polishing step in mAb purification, is able to clear both process-related impurities and product-related impurities. In this study, with the implementation of quality by design (QbD), a process development approach for robust removal of aggregates using CEX is described. First, resin screening studies were performed and a suitable CEX resin was chosen because of its relatively better selectivity and higher dynamic binding capacity. Second, a pH-conductivity hybrid gradient elution method for the CEX was established, and the risk assessment for the process was carried out. Third, a process characterization study was used to evaluate the impact of the potentially important process parameters on the process performance with respect to aggregate removal. Accordingly, a process design space was established. Aggregate level in load is the critical parameter. Its operating range is set at 0-3% and the acceptable range is set at 0-5%. Equilibration buffer is the key parameter. Its operating range is set at 40 ± 5 mM acetate, pH 5.0 ± 0.1, and acceptable range is set at 40 ± 10 mM acetate, pH 5.0 ± 0.2. Elution buffer, load mass, and gradient elution volume are non-key parameters; their operating ranges and acceptable ranges are equally set at 250 ± 10 mM acetate, pH 6.0 ± 0.2, 45 ± 10 g/L resin, and 10 ± 20% CV respectively. Finally, the process was scaled up 80 times and the impurities removal profiles were revealed. Three scaled-up runs showed that the size-exclusion chromatography (SEC) purity of the CEX pool was 99.8% or above and the step yield was above 92%, thereby proving that the process is both consistent and robust.

Processing of strong-motion accelerograms: Needs, options and consequences

USGS Publications Warehouse

Boore, D.M.; Bommer, J.J.

2005-01-01

Recordings from strong-motion accelerographs are of fundamental importance in earthquake engineering, forming the basis for all characterizations of ground shaking employed for seismic design. The recordings, particularly those from analog instruments, invariably contain noise that can mask and distort the ground-motion signal at both high and low frequencies. For any application of recorded accelerograms in engineering seismology or earthquake engineering, it is important to identify the presence of this noise in the digitized time-history and its influence on the parameters that are to be derived from the records. If the parameters of interest are affected by noise then appropriate processing needs to be applied to the records, although it must be accepted from the outset that it is generally not possible to recover the actual ground motion over a wide range of frequencies. There are many schemes available for processing strong-motion data and it is important to be aware of the merits and pitfalls associated with each option. Equally important is to appreciate the effects of the procedures on the records in order to avoid errors in the interpretation and use of the results. Options for processing strong-motion accelerograms are presented, discussed and evaluated from the perspective of engineering application. ?? 2004 Elsevier Ltd. All rights reserved.

Application of a data assimilation method via an ensemble Kalman filter to reactive urea hydrolysis transport modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Juxiu Tong; Bill X. Hu; Hai Huang

2014-03-01

With growing importance of water resources in the world, remediations of anthropogenic contaminations due to reactive solute transport become even more important. A good understanding of reactive rate parameters such as kinetic parameters is the key to accurately predicting reactive solute transport processes and designing corresponding remediation schemes. For modeling reactive solute transport, it is very difficult to estimate chemical reaction rate parameters due to complex processes of chemical reactions and limited available data. To find a method to get the reactive rate parameters for the reactive urea hydrolysis transport modeling and obtain more accurate prediction for the chemical concentrations,more » we developed a data assimilation method based on an ensemble Kalman filter (EnKF) method to calibrate reactive rate parameters for modeling urea hydrolysis transport in a synthetic one-dimensional column at laboratory scale and to update modeling prediction. We applied a constrained EnKF method to pose constraints to the updated reactive rate parameters and the predicted solute concentrations based on their physical meanings after the data assimilation calibration. From the study results we concluded that we could efficiently improve the chemical reactive rate parameters with the data assimilation method via the EnKF, and at the same time we could improve solute concentration prediction. The more data we assimilated, the more accurate the reactive rate parameters and concentration prediction. The filter divergence problem was also solved in this study.« less

A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

USGS Publications Warehouse

Ward, Adam S.; Kelleher, Christa A.; Mason, Seth J. K.; Wagener, Thorsten; McIntyre, Neil; McGlynn, Brian L.; Runkel, Robert L.; Payn, Robert A.

2017-01-01

Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.

Application of the Taguchi analytical method for optimization of effective parameters of the chemical vapor deposition process controlling the production of nanotubes/nanobeads.

PubMed

Sharon, Maheshwar; Apte, P R; Purandare, S C; Zacharia, Renju

2005-02-01

Seven variable parameters of the chemical vapor deposition system have been optimized with the help of the Taguchi analytical method for getting a desired product, e.g., carbon nanotubes or carbon nanobeads. It is observed that almost all selected parameters influence the growth of carbon nanotubes. However, among them, the nature of precursor (racemic, R or Technical grade camphor) and the carrier gas (hydrogen, argon and mixture of argon/hydrogen) seem to be more important parameters affecting the growth of carbon nanotubes. Whereas, for the growth of nanobeads, out of seven parameters, only two, i.e., catalyst (powder of iron, cobalt, and nickel) and temperature (1023 K, 1123 K, and 1273 K), are the most influential parameters. Systematic defects or islands on the substrate surface enhance nucleation of novel carbon materials. Quantitative contributions of process parameters as well as optimum factor levels are obtained by performing analysis of variance (ANOVA) and analysis of mean (ANOM), respectively.

Identification of open quantum systems from observable time traces

DOE PAGES

Zhang, Jun; Sarovar, Mohan

2015-05-27

Estimating the parameters that dictate the dynamics of a quantum system is an important task for quantum information processing and quantum metrology, as well as fundamental physics. In our paper we develop a method for parameter estimation for Markovian open quantum systems using a temporal record of measurements on the system. Furthermore, the method is based on system realization theory and is a generalization of our previous work on identification of Hamiltonian parameters.

Evaluation of laser cutting process with auxiliary gas pressure by soft computing approach

NASA Astrophysics Data System (ADS)

Lazov, Lyubomir; Nikolić, Vlastimir; Jovic, Srdjan; Milovančević, Miloš; Deneva, Heristina; Teirumenieka, Erika; Arsic, Nebojsa

2018-06-01

Evaluation of the optimal laser cutting parameters is very important for the high cut quality. This is highly nonlinear process with different parameters which is the main challenge in the optimization process. Data mining methodology is one of most versatile method which can be used laser cutting process optimization. Support vector regression (SVR) procedure is implemented since it is a versatile and robust technique for very nonlinear data regression. The goal in this study was to determine the optimal laser cutting parameters to ensure robust condition for minimization of average surface roughness. Three cutting parameters, the cutting speed, the laser power, and the assist gas pressure, were used in the investigation. As a laser type TruLaser 1030 technological system was used. Nitrogen as an assisted gas was used in the laser cutting process. As the data mining method, support vector regression procedure was used. Data mining prediction accuracy was very high according the coefficient (R2) of determination and root mean square error (RMSE): R2 = 0.9975 and RMSE = 0.0337. Therefore the data mining approach could be used effectively for determination of the optimal conditions of the laser cutting process.

Catchment process affecting drinking water quality, including the significance of rainfall events, using factor analysis and event mean concentrations.

PubMed

Cinque, Kathy; Jayasuriya, Niranjali

2010-12-01

To ensure the protection of drinking water an understanding of the catchment processes which can affect water quality is important as it enables targeted catchment management actions to be implemented. In this study factor analysis (FA) and comparing event mean concentrations (EMCs) with baseline values were techniques used to asses the relationships between water quality parameters and linking those parameters to processes within an agricultural drinking water catchment. FA found that 55% of the variance in the water quality data could be explained by the first factor, which was dominated by parameters usually associated with erosion. Inclusion of pathogenic indicators in an additional FA showed that Enterococcus and Clostridium perfringens (C. perfringens) were also related to the erosion factor. Analysis of the EMCs found that most parameters were significantly higher during periods of rainfall runoff. This study shows that the most dominant processes in an agricultural catchment are surface runoff and erosion. It also shows that it is these processes which mobilise pathogenic indicators and are therefore most likely to influence the transport of pathogens. Catchment management efforts need to focus on reducing the effect of these processes on water quality.

X-31 aerodynamic characteristics determined from flight data

NASA Technical Reports Server (NTRS)

Kokolios, Alex

1993-01-01

The lateral aerodynamic characteristics of the X-31 were determined at angles of attack ranging from 20 to 45 deg. Estimates of the lateral stability and control parameters were obtained by applying two parameter estimation techniques, linear regression, and the extended Kalman filter to flight test data. An attempt to apply maximum likelihood to extract parameters from the flight data was also made but failed for the reasons presented. An overview of the System Identification process is given. The overview includes a listing of the more important properties of all three estimation techniques that were applied to the data. A comparison is given of results obtained from flight test data and wind tunnel data for four important lateral parameters. Finally, future research to be conducted in this area is discussed.

On the interpretation of weight vectors of linear models in multivariate neuroimaging.

PubMed

Haufe, Stefan; Meinecke, Frank; Görgen, Kai; Dähne, Sven; Haynes, John-Dylan; Blankertz, Benjamin; Bießmann, Felix

2014-02-15

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Examining Mechanical Strength Characteristics of Selective Inhibition Sintered HDPE Specimens Using RSM and Desirability Approach

NASA Astrophysics Data System (ADS)

Rajamani, D.; Esakki, Balasubramanian

2017-09-01

Selective inhibition sintering (SIS) is a powder based additive manufacturing (AM) technique to produce functional parts with an inexpensive system compared with other AM processes. Mechanical properties of SIS fabricated parts are of high dependence on various process parameters importantly layer thickness, heat energy, heater feedrate, and printer feedrate. In this paper, examining the influence of these process parameters on evaluating mechanical properties such as tensile and flexural strength using Response Surface Methodology (RSM) is carried out. The test specimens are fabricated using high density polyethylene (HDPE) and mathematical models are developed to correlate the control factors to the respective experimental design response. Further, optimal SIS process parameters are determined using desirability approach to enhance the mechanical properties of HDPE specimens. Optimization studies reveal that, combination of high heat energy, low layer thickness, medium heater feedrate and printer feedrate yielded superior mechanical strength characteristics.

The dynamics of Black Smokers: a heated-salty plume analog.

NASA Astrophysics Data System (ADS)

Maxworthy, Tony

2004-11-01

Experiments have been carried out on the dynamical processes that govern the evolution of hot, salty plumes injected into cold surroundings. Under the appropriate circumstances these are then used as an analoque system to understand some features of particle-laden, deep-ocean, hydrothermal plumes, e.g., Black Smokers. Details of the temperature distributions over a wide range of parameters are presented and these, coupled with flow visualization experiments, have yielded a fairly complete picture of the important features of the flow. As a result it has been concluded that cabelling processes are critical to an understanding of the flow reversals found in a certain parameter range and that double diffusive processes, though present, are of minor importance. As a final exercise an example is worked through in which the circumstances for flow reversal in deep-sea plumes have been estimated based on the best available knowledge of these interesting entities.

Parameter optimization of flux-aided backing-submerged arc welding by using Taguchi method

NASA Astrophysics Data System (ADS)

Pu, Juan; Yu, Shengfu; Li, Yuanyuan

2017-07-01

Flux-aided backing-submerged arc welding has been conducted on D36 steel with thickness of 20 mm. The effects of processing parameters such as welding current, voltage, welding speed and groove angle on welding quality were investigated by Taguchi method. The optimal welding parameters were predicted and the individual importance of each parameter on welding quality was evaluated by examining the signal-to-noise ratio and analysis of variance (ANOVA) results. The importance order of the welding parameters for the welding quality of weld bead was: welding current > welding speed > groove angle > welding voltage. The welding quality of weld bead increased gradually with increasing welding current and welding speed and decreasing groove angle. The optimum values of the welding current, welding speed, groove angle and welding voltage were found to be 1050 A, 27 cm/min, 40∘ and 34 V, respectively.

A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

PubMed

Choi, D J; Park, H

2001-11-01

For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

Latent variable modeling to analyze the effects of process parameters on the dissolution of paracetamol tablet

PubMed Central

Sun, Fei; Xu, Bing; Zhang, Yi; Dai, Shengyun; Shi, Xinyuan; Qiao, Yanjiang

2017-01-01

ABSTRACT The dissolution is one of the critical quality attributes (CQAs) of oral solid dosage forms because it relates to the absorption of drug. In this paper, the influence of raw materials, granules and process parameters on the dissolution of paracetamol tablet was analyzed using latent variable modeling methods. The variability in raw materials and granules was understood based on the principle component analysis (PCA), respectively. A multi-block partial least squares (MBPLS) model was used to determine the critical factors affecting the dissolution. The results showed that the binder amount, the post granulation time, the API content in granule, the fill depth and the punch tip separation distance were the critical factors with variable importance in the projection (VIP) values larger than 1. The importance of each unit of the whole process was also ranked using the block importance in the projection (BIP) index. It was concluded that latent variable models (LVMs) were very useful tools to extract information from the available data and improve the understanding on dissolution behavior of paracetamol tablet. The obtained LVMs were also helpful to propose the process design space and to design control strategies in the further research. PMID:27689242

Parameter-induced uncertainty quantification of crop yields, soil N2O and CO2 emission for 8 arable sites across Europe using the LandscapeDNDC model

NASA Astrophysics Data System (ADS)

Santabarbara, Ignacio; Haas, Edwin; Kraus, David; Herrera, Saul; Klatt, Steffen; Kiese, Ralf

2014-05-01

When using biogeochemical models to estimate greenhouse gas emissions at site to regional/national levels, the assessment and quantification of the uncertainties of simulation results are of significant importance. The uncertainties in simulation results of process-based ecosystem models may result from uncertainties of the process parameters that describe the processes of the model, model structure inadequacy as well as uncertainties in the observations. Data for development and testing of uncertainty analisys were corp yield observations, measurements of soil fluxes of nitrous oxide (N2O) and carbon dioxide (CO2) from 8 arable sites across Europe. Using the process-based biogeochemical model LandscapeDNDC for simulating crop yields, N2O and CO2 emissions, our aim is to assess the simulation uncertainty by setting up a Bayesian framework based on Metropolis-Hastings algorithm. Using Gelman statistics convergence criteria and parallel computing techniques, enable multi Markov Chains to run independently in parallel and create a random walk to estimate the joint model parameter distribution. Through means distribution we limit the parameter space, get probabilities of parameter values and find the complex dependencies among them. With this parameter distribution that determines soil-atmosphere C and N exchange, we are able to obtain the parameter-induced uncertainty of simulation results and compare them with the measurements data.

Optimization of pulsed laser welding process parameters in order to attain minimum underfill and undercut defects in thin 316L stainless steel foils

NASA Astrophysics Data System (ADS)

Pakmanesh, M. R.; Shamanian, M.

2018-02-01

In this study, the optimization of pulsed Nd:YAG laser welding parameters was done on the lap-joint of a 316L stainless steel foil with the aim of reducing weld defects through response surface methodology. For this purpose, the effects of peak power, pulse-duration, and frequency were investigated. The most important weld defects seen in this method include underfill and undercut. By presenting a second-order polynomial, the above-mentioned statistical method was managed to be well employed to balance the welding parameters. The results showed that underfill increased with the increased power and reduced frequency, it first increased and then decreased with the increased pulse-duration; and the most important parameter affecting it was the power, whose effect was 65%. The undercut increased with the increased power, pulse-duration, and frequency; and the most important parameter affecting it was the power, whose effect was 64%. Finally, by superimposing different responses, improved conditions were presented to attain a weld with no defects.

Systematic procedure for designing processes with multiple environmental objectives.

PubMed

Kim, Ki-Joo; Smith, Raymond L

2005-04-01

Evaluation of multiple objectives is very important in designing environmentally benign processes. It requires a systematic procedure for solving multiobjective decision-making problems due to the complex nature of the problems, the need for complex assessments, and the complicated analysis of multidimensional results. In this paper, a novel systematic procedure is presented for designing processes with multiple environmental objectives. This procedure has four steps: initialization, screening, evaluation, and visualization. The first two steps are used for systematic problem formulation based on mass and energy estimation and order of magnitude analysis. In the third step, an efficient parallel multiobjective steady-state genetic algorithm is applied to design environmentally benign and economically viable processes and to provide more accurate and uniform Pareto optimal solutions. In the last step a new visualization technique for illustrating multiple objectives and their design parameters on the same diagram is developed. Through these integrated steps the decision-maker can easily determine design alternatives with respect to his or her preferences. Most importantly, this technique is independent of the number of objectives and design parameters. As a case study, acetic acid recovery from aqueous waste mixtures is investigated by minimizing eight potential environmental impacts and maximizing total profit. After applying the systematic procedure, the most preferred design alternatives and their design parameters are easily identified.

Data quality system using reference dictionaries and edit distance algorithms

NASA Astrophysics Data System (ADS)

Karbarz, Radosław; Mulawka, Jan

2015-09-01

The real art of management it is important to make smart decisions, what in most of the cases is not a trivial task. Those decisions may lead to determination of production level, funds allocation for investments etc. Most of the parameters in decision-making process such as: interest rate, goods value or exchange rate may change. It is well know that these parameters in the decision-making are based on the data contained in datamarts or data warehouse. However, if the information derived from the processed data sets is the basis for the most important management decisions, it is required that the data is accurate, complete and current. In order to achieve high quality data and to gain from them measurable business benefits, data quality system should be used. The article describes the approach to the problem, shows the algorithms in details and their usage. Finally the test results are provide. Test results show the best algorithms (in terms of quality and quantity) for different parameters and data distribution.

Using implicit association tests in age-heterogeneous samples: The importance of cognitive abilities and quad model processes.

PubMed

Wrzus, Cornelia; Egloff, Boris; Riediger, Michaela

2017-08-01

Implicit association tests (IATs) are increasingly used to indirectly assess people's traits, attitudes, or other characteristics. In addition to measuring traits or attitudes, IAT scores also reflect differences in cognitive abilities because scores are based on reaction times (RTs) and errors. As cognitive abilities change with age, questions arise concerning the usage and interpretation of IATs for people of different age. To address these questions, the current study examined how cognitive abilities and cognitive processes (i.e., quad model parameters) contribute to IAT results in a large age-heterogeneous sample. Participants (N = 549; 51% female) in an age-stratified sample (range = 12-88 years) completed different IATs and 2 tasks to assess cognitive processing speed and verbal ability. From the IAT data, D2-scores were computed based on RTs, and quad process parameters (activation of associations, overcoming bias, detection, guessing) were estimated from individual error rates. Substantial IAT scores and quad processes except guessing varied with age. Quad processes AC and D predicted D2-scores of the content-specific IAT. Importantly, the effects of cognitive abilities and quad processes on IAT scores were not significantly moderated by participants' age. These findings suggest that IATs seem suitable for age-heterogeneous studies from adolescence to old age when IATs are constructed and analyzed appropriately, for example with D-scores and process parameters. We offer further insight into how D-scoring controls for method effects in IATs and what IAT scores capture in addition to implicit representations of characteristics. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

TWT transmitter fault prediction based on ANFIS

NASA Astrophysics Data System (ADS)

Li, Mengyan; Li, Junshan; Li, Shuangshuang; Wang, Wenqing; Li, Fen

2017-11-01

Fault prediction is an important component of health management, and plays an important role in the reliability guarantee of complex electronic equipments. Transmitter is a unit with high failure rate. The cathode performance of TWT is a common fault of transmitter. In this dissertation, a model based on a set of key parameters of TWT is proposed. By choosing proper parameters and applying adaptive neural network training model, this method, combined with analytic hierarchy process (AHP), has a certain reference value for the overall health judgment of TWT transmitters.

Development of quantitative radioactive methodologies on paper to determine important lateral-flow immunoassay parameters.

PubMed

Mosley, Garrett L; Nguyen, Phuong; Wu, Benjamin M; Kamei, Daniel T

2016-08-07

The lateral-flow immunoassay (LFA) is a well-established diagnostic technology that has recently seen significant advancements due in part to the rapidly expanding fields of paper diagnostics and paper-fluidics. As LFA-based diagnostics become more complex, it becomes increasingly important to quantitatively determine important parameters during the design and evaluation process. However, current experimental methods for determining these parameters have certain limitations when applied to LFA systems. In this work, we describe our novel methods of combining paper and radioactive measurements to determine nanoprobe molarity, the number of antibodies per nanoprobe, and the forward and reverse rate constants for nanoprobe binding to immobilized target on the LFA test line. Using a model LFA system that detects for the presence of the protein transferrin (Tf), we demonstrate the application of our methods, which involve quantitative experimentation and mathematical modeling. We also compare the results of our rate constant experiments with traditional experiments to demonstrate how our methods more appropriately capture the influence of the LFA environment on the binding interaction. Our novel experimental approaches can therefore more efficiently guide the research process for LFA design, leading to more rapid advancement of the field of paper-based diagnostics.

A method to optimize the processing algorithm of a computed radiography system for chest radiography.

PubMed

Moore, C S; Liney, G P; Beavis, A W; Saunderson, J R

2007-09-01

A test methodology using an anthropomorphic-equivalent chest phantom is described for the optimization of the Agfa computed radiography "MUSICA" processing algorithm for chest radiography. The contrast-to-noise ratio (CNR) in the lung, heart and diaphragm regions of the phantom, and the "system modulation transfer function" (sMTF) in the lung region, were measured using test tools embedded in the phantom. Using these parameters the MUSICA processing algorithm was optimized with respect to low-contrast detectability and spatial resolution. Two optimum "MUSICA parameter sets" were derived respectively for maximizing the CNR and sMTF in each region of the phantom. Further work is required to find the relative importance of low-contrast detectability and spatial resolution in chest images, from which the definitive optimum MUSICA parameter set can then be derived. Prior to this further work, a compromised optimum MUSICA parameter set was applied to a range of clinical images. A group of experienced image evaluators scored these images alongside images produced from the same radiographs using the MUSICA parameter set in clinical use at the time. The compromised optimum MUSICA parameter set was shown to produce measurably better images.

Application of Multi-Parameter Data Visualization by Means of Multidimensional Scaling to Evaluate Possibility of Coal Gasification

NASA Astrophysics Data System (ADS)

Jamróz, Dariusz; Niedoba, Tomasz; Surowiak, Agnieszka; Tumidajski, Tadeusz; Szostek, Roman; Gajer, Mirosław

2017-09-01

The application of methods drawing upon multi-parameter visualization of data by transformation of multidimensional space into two-dimensional one allow to show multi-parameter data on computer screen. Thanks to that, it is possible to conduct a qualitative analysis of this data in the most natural way for human being, i.e. by the sense of sight. An example of such method of multi-parameter visualization is multidimensional scaling. This method was used in this paper to present and analyze a set of seven-dimensional data obtained from Janina Mining Plant and Wieczorek Coal Mine. It was decided to examine whether the method of multi-parameter data visualization allows to divide the samples space into areas of various applicability to fluidal gasification process. The "Technological applicability card for coals" was used for this purpose [Sobolewski et al., 2012; 2017], in which the key parameters, important and additional ones affecting the gasification process were described.

Dimensionless Analysis and Mathematical Modeling of Electromagnetic Levitation (EML) of Metals

NASA Astrophysics Data System (ADS)

Gao, Lei; Shi, Zhe; Li, Donghui; Yang, Yindong; Zhang, Guifang; McLean, Alexander; Chattopadhyay, Kinnor

2016-02-01

Electromagnetic levitation (EML), a contactless metal melting method, can be used to produce ultra-pure metals and alloys. In the EML process, the levitation force exerted on the droplet is of paramount importance and is affected by many parameters. In this paper, the relationship between levitation force and parameters affecting the levitation process were investigated by dimensionless analysis. The general formula developed by dimensionless analysis was tested and evaluated by numerical modeling. This technique can be employed to design levitation systems for a variety of materials.

Development of system design information for carbon dioxide using an amine type sorber

NASA Technical Reports Server (NTRS)

Rankin, R. L.; Roehlich, F.; Vancheri, F.

1971-01-01

Development work on system design information for amine type carbon dioxide sorber is reported. Amberlite IR-45, an aminated styrene divinyl benzene matrix, was investigated to determine the influence of design parameters of sorber particle size, process flow rate, CO2 partial pressure, total pressure, and bed designs. CO2 capacity and energy requirements for a 4-man size system were related mathematically to important operational parameters. Some fundamental studies in CO2 sorber capacity, energy requirements, and process operation were also performed.

Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets.

PubMed

Sun, Fei; Xu, Bing; Zhang, Yi; Dai, Shengyun; Yang, Chan; Cui, Xianglong; Shi, Xinyuan; Qiao, Yanjiang

2016-01-01

The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules' properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet.

Magnetorheological finishing: a perfect solution to nanofinishing requirements

NASA Astrophysics Data System (ADS)

Sidpara, Ajay

2014-09-01

Finishing of optics for different applications is the most important as well as difficult step to meet the specification of optics. Conventional grinding or other polishing processes are not able to reduce surface roughness beyond a certain limit due to high forces acting on the workpiece, embedded abrasive particles, limited control over process, etc. Magnetorheological finishing (MRF) process provides a new, efficient, and innovative way to finish optical materials as well many metals to their desired level of accuracy. This paper provides an overview of MRF process for different applications, important process parameters, requirement of magnetorheological fluid with respect to workpiece material, and some areas that need to be explored for extending the application of MRF process.

The Importance of Parameter Variances, Correlations Lengths, and Cross-Correlations in Reactive Transport Models: Key Considerations for Assessing the Need for Microscale Information (Invited)

NASA Astrophysics Data System (ADS)

Reimus, P. W.

2010-12-01

A process-oriented modeling approach is implemented to examine the importance of parameter variances, correlation lengths, and especially cross-correlations in contaminant transport predictions over large scales. It is shown that the most important consideration is the correlation between flow rates and retardation processes (e.g., sorption, matrix diffusion) in the system. If flow rates are negatively correlated with retardation factors in systems containing multiple flow pathways, then characterizing these negative correlation(s) may have more impact on reactive transport modeling than microscale information. Such negative correlations are expected in porous-media systems where permeability is negatively correlated with clay content and rock alteration (which are usually associated with increased sorption). Likewise, negative correlations are expected in fractured rocks where permeability is positively correlated with fracture apertures, which in turn are negatively correlated with sorption and matrix diffusion. Parameter variances and correlation lengths are also shown to have important effects on reactive transport predictions, but they are less important than parameter cross-correlations. Microscale information pertaining to contaminant transport has become more readily available as characterization methods and spectroscopic instrumentation have achieved lower detection limits, greater resolution, and better precision. Obtaining detailed mechanistic insights into contaminant-rock-water interactions is becoming a routine practice in characterizing reactive transport processes in groundwater systems (almost necessary for high-profile publications). Unfortunately, a quantitative link between microscale information and flow and transport parameter distributions or cross-correlations has not yet been established. One reason for this is that quantitative microscale information is difficult to obtain in complex, heterogeneous systems, so simple systems that lack the complexity and heterogeneity of real aquifer materials are often studied. Another is that instrumentation used to obtain microscale information often probes only one variable or family of variables at a time, so linkages to other variables must be inferred by indirect means from other lines of evidence. Despite these limitations, microscale information can be useful in the development and validation of reactive transport models. For example, knowledge of mineral phases that have strong affinities for contaminants can help in the development of cross-correlations between flow and sorption parameters via characterization of permeability and mineral distributions in aquifers. Likewise, microscale information on pore structures in low-permeability zones and contaminant penetration distances into these zones from higher-permeability zones (e.g., fractures) can provide valuable constraints on the representation of diffusive mass transfer processes between flowing porosity and secondary porosity. The prioritization of obtaining microscale information in any groundwater system can be informed by modeling exercises such as those conducted for this study.

Direct Metal Deposition of H13 Tool Steel on Copper Alloy Substrate: Parametric Investigation

NASA Astrophysics Data System (ADS)

Imran, M. Khalid; Masood, S. H.; Brandt, Milan

2015-12-01

Over the past decade, researchers have demonstrated interest in tribology and prototyping by the laser aided material deposition process. Laser aided direct metal deposition (DMD) enables the formation of a uniform clad by melting the powder to form desired component from metal powder materials. In this research H13 tool steel has been used to clad on a copper alloy substrate using DMD. The effects of laser parameters on the quality of DMD deposited clad have been investigated and acceptable processing parameters have been determined largely through trial-and-error approaches. The relationships between DMD process parameters and the product characteristics such as porosity, micro-cracks and microhardness have been analysed using scanning electron microscope (SEM), image analysis software (ImageJ) and microhardness tester. It has been found that DMD parameters such as laser power, powder mass flow rate, feed rate and focus size have an important role in clad quality and crack formation.

[Parameters of cardiac muscle repolarization on the electrocardiogram when changing anatomical and electric position of the heart].

PubMed

Chaĭkovskiĭ, I A; Baum, O V; Popov, L A; Voloshin, V I; Budnik, N N; Frolov, Iu A; Kovalenko, A S

2014-01-01

While discussing the diagnostic value of the single channel electrocardiogram a set of theoretical considerations emerges inevitably, one of the most important among them is the question about dependence of the electrocardiogram parameters from the direction of electrical axis of heart. In other words, changes in what of electrocardiogram parameters are in fact liable to reflect pathological processes in myocardium, and what ones are determined by extracardiac factors, primarily by anatomic characteristics of patients. It is arguable that while analyzing electrocardiogram it is necessary to orient to such physiologically based informative indexes as ST segment displacement. Also, symmetry of the T wave shape is an important parameter which is independent of patients anatomic features. The results obtained are of interest for theoretical and applied aspects of the biophysics of the cardiac electric field.

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

Estimation of Power Consumption in the Circular Sawing of Stone Based on Tangential Force Distribution

NASA Astrophysics Data System (ADS)

Huang, Guoqin; Zhang, Meiqin; Huang, Hui; Guo, Hua; Xu, Xipeng

2018-04-01

Circular sawing is an important method for the processing of natural stone. The ability to predict sawing power is important in the optimisation, monitoring and control of the sawing process. In this paper, a predictive model (PFD) of sawing power, which is based on the tangential force distribution at the sawing contact zone, was proposed, experimentally validated and modified. With regard to the influence of sawing speed on tangential force distribution, the modified PFD (MPFD) performed with high predictive accuracy across a wide range of sawing parameters, including sawing speed. The mean maximum absolute error rate was within 6.78%, and the maximum absolute error rate was within 11.7%. The practicability of predicting sawing power by the MPFD with few initial experimental samples was proved in case studies. On the premise of high sample measurement accuracy, only two samples are required for a fixed sawing speed. The feasibility of applying the MPFD to optimise sawing parameters while lowering the energy consumption of the sawing system was validated. The case study shows that energy use was reduced 28% by optimising the sawing parameters. The MPFD model can be used to predict sawing power, optimise sawing parameters and control energy.

Some Physical Parameters to Effect the Production of Heamatococcus pluvialis

NASA Astrophysics Data System (ADS)

Akpolat, O.; Eristurk, S.

The aim of this study is to optimize the physical parameters affecting the production of Haematococcus pluvialis in photobioreactors and to simulate the process. Heamatococcus pluvialis is a green microalgea to have a great interest for production of natural astaxanthin and it can be cultivated in a closed photobiorector system under controlled conditions. Biomass composition, growth rate and high value product spectra like polyunsaturated fatty acids, pigments, poly saccariydes or vitamins depend on strongly the parameters of cultivation process. These are composition of cultivation medium, mixing model and aeration rate, hydrodynamic stress of medium which can be changed by adding some chemicals, cultivation temperature, pH, carbon dioxide and oxygen supply and most important of all: illumination. One of the most important problems during the cultivation is that cells have sensitivity to shear stress very much and the shear stress created by aeration and mixing effects the growth rate of the cell negatively and decreases yield. In this study, physical parameters such as; the rate of the air fed into the reactor, the mixing type, the reduction of the hydrodynamic stress by CMC addition, the effect of the cell size on the cell production and the flocculation speed of the culture, were investigated.

Influence of Wire Electrical Discharge Machining (WEDM) process parameters on surface roughness

NASA Astrophysics Data System (ADS)

Yeakub Ali, Mohammad; Banu, Asfana; Abu Bakar, Mazilah

2018-01-01

In obtaining the best quality of engineering components, the quality of machined parts surface plays an important role. It improves the fatigue strength, wear resistance, and corrosion of workpiece. This paper investigates the effects of wire electrical discharge machining (WEDM) process parameters on surface roughness of stainless steel using distilled water as dielectric fluid and brass wire as tool electrode. The parameters selected are voltage open, wire speed, wire tension, voltage gap, and off time. Empirical model was developed for the estimation of surface roughness. The analysis revealed that off time has a major influence on surface roughness. The optimum machining parameters for minimum surface roughness were found to be at a 10 V open voltage, 2.84 μs off time, 12 m/min wire speed, 6.3 N wire tension, and 54.91 V voltage gap.

Surface pretreatment of plastics with an atmospheric pressure plasma jet - Influence of generator power and kinematics

NASA Astrophysics Data System (ADS)

Moritzer, E.; Leister, C.

2014-05-01

The industrial use of atmospheric pressure plasmas in the plastics processing industry has increased significantly in recent years. Users of this treatment process have the possibility to influence the target values (e.g. bond strength or surface energy) with the help of kinematic and electrical parameters. Until now, systematic procedures have been used with which the parameters can be adapted to the process or product requirements but only by very time-consuming methods. For this reason, the relationship between influencing values and target values will be examined based on the example of a pretreatment in the bonding process with the help of statistical experimental design. Because of the large number of parameters involved, the analysis is restricted to the kinematic and electrical parameters. In the experimental tests, the following factors are taken as parameters: gap between nozzle and substrate, treatment velocity (kinematic data), voltage and duty cycle (electrical data). The statistical evaluation shows significant relationships between the parameters and surface energy in the case of polypropylene. An increase in the voltage and duty cycle increases the polar proportion of the surface energy, while a larger gap and higher velocity leads to lower energy levels. The bond strength of the overlapping bond is also significantly influenced by the voltage, velocity and gap. The direction of their effects is identical with those of the surface energy. In addition to the kinematic influences of the motion of an atmospheric pressure plasma jet, it is therefore especially important that the parameters for the plasma production are taken into account when designing the pretreatment processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moritzer, E., E-mail: elmar.moritzer@ktp.upb.de; Leister, C., E-mail: elmar.moritzer@ktp.upb.de

The industrial use of atmospheric pressure plasmas in the plastics processing industry has increased significantly in recent years. Users of this treatment process have the possibility to influence the target values (e.g. bond strength or surface energy) with the help of kinematic and electrical parameters. Until now, systematic procedures have been used with which the parameters can be adapted to the process or product requirements but only by very time-consuming methods. For this reason, the relationship between influencing values and target values will be examined based on the example of a pretreatment in the bonding process with the help ofmore » statistical experimental design. Because of the large number of parameters involved, the analysis is restricted to the kinematic and electrical parameters. In the experimental tests, the following factors are taken as parameters: gap between nozzle and substrate, treatment velocity (kinematic data), voltage and duty cycle (electrical data). The statistical evaluation shows significant relationships between the parameters and surface energy in the case of polypropylene. An increase in the voltage and duty cycle increases the polar proportion of the surface energy, while a larger gap and higher velocity leads to lower energy levels. The bond strength of the overlapping bond is also significantly influenced by the voltage, velocity and gap. The direction of their effects is identical with those of the surface energy. In addition to the kinematic influences of the motion of an atmospheric pressure plasma jet, it is therefore especially important that the parameters for the plasma production are taken into account when designing the pretreatment processes.« less

Etching Behavior of Aluminum Alloy Extrusions

NASA Astrophysics Data System (ADS)

Zhu, Hanliang

2014-11-01

The etching treatment is an important process step in influencing the surface quality of anodized aluminum alloy extrusions. The aim of etching is to produce a homogeneously matte surface. However, in the etching process, further surface imperfections can be generated on the extrusion surface due to uneven materials loss from different microstructural components. These surface imperfections formed prior to anodizing can significantly influence the surface quality of the final anodized extrusion products. In this article, various factors that influence the materials loss during alkaline etching of aluminum alloy extrusions are investigated. The influencing variables considered include etching process parameters, Fe-rich particles, Mg-Si precipitates, and extrusion profiles. This study provides a basis for improving the surface quality in industrial extrusion products by optimizing various process parameters.

An improved probit method for assessment of domino effect to chemical process equipment caused by overpressure.

PubMed

Mingguang, Zhang; Juncheng, Jiang

2008-10-30

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Damage probability and relative threshold value are two necessary parameters in QRA of this phenomenon. Some simple models had been proposed based on scarce data or oversimplified assumption. Hence, more data about damage to chemical process equipments were gathered and analyzed, a quantitative relationship between damage probability and damage degrees of equipment was built, and reliable probit models were developed associated to specific category of chemical process equipments. Finally, the improvements of present models were evidenced through comparison with other models in literatures, taking into account such parameters: consistency between models and data, depth of quantitativeness in QRA.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Classical nucleation theory of homogeneous freezing of water: thermodynamic and kinetic parameters.

PubMed

Ickes, Luisa; Welti, André; Hoose, Corinna; Lohmann, Ulrike

2015-02-28

The probability of homogeneous ice nucleation under a set of ambient conditions can be described by nucleation rates using the theoretical framework of Classical Nucleation Theory (CNT). This framework consists of kinetic and thermodynamic parameters, of which three are not well-defined (namely the interfacial tension between ice and water, the activation energy and the prefactor), so that any CNT-based parameterization of homogeneous ice formation is less well-constrained than desired for modeling applications. Different approaches to estimate the thermodynamic and kinetic parameters of CNT are reviewed in this paper and the sensitivity of the calculated nucleation rate to the choice of parameters is investigated. We show that nucleation rates are very sensitive to this choice. The sensitivity is governed by one parameter - the interfacial tension between ice and water, which determines the energetic barrier of the nucleation process. The calculated nucleation rate can differ by more than 25 orders of magnitude depending on the choice of parameterization for this parameter. The second most important parameter is the activation energy of the nucleation process. It can lead to a variation of 16 orders of magnitude. By estimating the nucleation rate from a collection of droplet freezing experiments from the literature, the dependence of these two parameters on temperature is narrowed down. It can be seen that the temperature behavior of these two parameters assumed in the literature does not match with the predicted nucleation rates from the fit in most cases. Moreover a comparison of all possible combinations of theoretical parameterizations of the dominant two free parameters shows that one combination fits the fitted nucleation rates best, which is a description of the interfacial tension coming from a molecular model [Reinhardt and Doye, J. Chem. Phys., 2013, 139, 096102] in combination with the activation energy derived from self-diffusion measurements [Zobrist et al., J. Phys. Chem. C, 2007, 111, 2149]. However, some fundamental understanding of the processes is still missing. Further research in future might help to tackle this problem. The most important questions, which need to be answered to constrain CNT, are raised in this study.

Identification of the most sensitive parameters in the activated sludge model implemented in BioWin software.

PubMed

Liwarska-Bizukojc, Ewa; Biernacki, Rafal

2010-10-01

In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.

An Improved Method to Control the Critical Parameters of a Multivariable Control System

NASA Astrophysics Data System (ADS)

Subha Hency Jims, P.; Dharmalingam, S.; Wessley, G. Jims John

2017-10-01

The role of control systems is to cope with the process deficiencies and the undesirable effect of the external disturbances. Most of the multivariable processes are highly iterative and complex in nature. Aircraft systems, Modern Power Plants, Refineries, Robotic systems are few such complex systems that involve numerous critical parameters that need to be monitored and controlled. Control of these important parameters is not only tedious and cumbersome but also is crucial from environmental, safety and quality perspective. In this paper, one such multivariable system, namely, a utility boiler has been considered. A modern power plant is a complex arrangement of pipework and machineries with numerous interacting control loops and support systems. In this paper, the calculation of controller parameters based on classical tuning concepts has been presented. The controller parameters thus obtained and employed has controlled the critical parameters of a boiler during fuel switching disturbances. The proposed method can be applied to control the critical parameters like elevator, aileron, rudder, elevator trim rudder and aileron trim, flap control systems of aircraft systems.

Multi-surface topography targeted plateau honing for the processing of cylinder liner surfaces of automotive engines

NASA Astrophysics Data System (ADS)

Lawrence, K. Deepak; Ramamoorthy, B.

2016-03-01

Cylinder bores of automotive engines are 'engineered' surfaces that are processed using multi-stage honing process to generate multiple layers of micro geometry for meeting the different functional requirements of the piston assembly system. The final processed surfaces should comply with several surface topographic specifications that are relevant for the good tribological performance of the engine. Selection of the process parameters in three stages of honing to obtain multiple surface topographic characteristics simultaneously within the specification tolerance is an important module of the process planning and is often posed as a challenging task for the process engineers. This paper presents a strategy by combining the robust process design and gray-relational analysis to evolve the operating levels of honing process parameters in rough, finish and plateau honing stages targeting to meet multiple surface topographic specifications on the final running surface of the cylinder bores. Honing experiments were conducted in three stages namely rough, finish and plateau honing on cast iron cylinder liners by varying four honing process parameters such as rotational speed, oscillatory speed, pressure and honing time. Abbott-Firestone curve based functional parameters (Rk, Rpk, Rvk, Mr1 and Mr2) coupled with mean roughness depth (Rz, DIN/ISO) and honing angle were measured and identified as the surface quality performance targets to be achieved. The experimental results have shown that the proposed approach is effective to generate cylinder liner surface that would simultaneously meet the explicit surface topographic specifications currently practiced by the industry.

Comparison of different filter methods for data assimilation in the unsaturated zone

NASA Astrophysics Data System (ADS)

Lange, Natascha; Berkhahn, Simon; Erdal, Daniel; Neuweiler, Insa

2016-04-01

The unsaturated zone is an important compartment, which plays a role for the division of terrestrial water fluxes into surface runoff, groundwater recharge and evapotranspiration. For data assimilation in coupled systems it is therefore important to have a good representation of the unsaturated zone in the model. Flow processes in the unsaturated zone have all the typical features of flow in porous media: Processes can have long memory and as observations are scarce, hydraulic model parameters cannot be determined easily. However, they are important for the quality of model predictions. On top of that, the established flow models are highly non-linear. For these reasons, the use of the popular Ensemble Kalman filter as a data assimilation method to estimate state and parameters in unsaturated zone models could be questioned. With respect to the long process memory in the subsurface, it has been suggested that iterative filters and smoothers may be more suitable for parameter estimation in unsaturated media. We test the performance of different iterative filters and smoothers for data assimilation with a focus on parameter updates in the unsaturated zone. In particular we compare the Iterative Ensemble Kalman Filter and Smoother as introduced by Bocquet and Sakov (2013) as well as the Confirming Ensemble Kalman Filter and the modified Restart Ensemble Kalman Filter proposed by Song et al. (2014) to the original Ensemble Kalman Filter (Evensen, 2009). This is done with simple test cases generated numerically. We consider also test examples with layering structure, as a layering structure is often found in natural soils. We assume that observations are water content, obtained from TDR probes or other observation methods sampling relatively small volumes. Particularly in larger data assimilation frameworks, a reasonable balance between computational effort and quality of results has to be found. Therefore, we compare computational costs of the different methods as well as the quality of open loop model predictions and the estimated parameters. Bocquet, M. and P. Sakov, 2013: Joint state and parameter estimation with an iterative ensemble Kalman smoother, Nonlinear Processes in Geophysics 20(5): 803-818. Evensen, G., 2009: Data assimilation: The ensemble Kalman filter. Springer Science & Business Media. Song, X.H., L.S. Shi, M. Ye, J.Z. Yang and I.M. Navon, 2014: Numerical comparison of iterative ensemble Kalman filters for unsaturated flow inverse modeling. Vadose Zone Journal 13(2), 10.2136/vzj2013.05.0083.

Behavioral Feature Extraction to Determine Learning Styles in e-Learning Environments

ERIC Educational Resources Information Center

Fatahi, Somayeh; Moradi, Hadi; Farmad, Elaheh

2015-01-01

Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of…

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

PubMed

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Consumer perception of dry-cured sheep meat products: Influence of process parameters under different evoked contexts.

PubMed

de Andrade, Juliana Cunha; Nalério, Elen Silveira; Giongo, Citieli; de Barcellos, Marcia Dutra; Ares, Gastón; Deliza, Rosires

2017-08-01

The development of high-quality air-dried cured sheep meat products adapted to meet consumer demands represent an interesting option to add value to the meat of adult animals. The present study aimed to evaluate the influence of process parameters on consumer choice of two products from sheep meat under different evoked contexts, considering product concepts. A total of 375 Brazilian participants completed a choice-based conjoint task with three 2-level variables for each product: maturation time, smoking, and sodium reduction for dry-cured sheep ham, and natural antioxidant, smoking, and sodium reduction for sheep meat coppa. A between-subjects experimental design was used to evaluate the influence of consumption context on consumer choices. All the process parameters significantly influenced consumer choice. However, their relative importance was affected by evoked context. Copyright © 2017. Published by Elsevier Ltd.

Multiple-objective optimization in precision laser cutting of different thermoplastics

NASA Astrophysics Data System (ADS)

Tamrin, K. F.; Nukman, Y.; Choudhury, I. A.; Shirley, S.

2015-04-01

Thermoplastics are increasingly being used in biomedical, automotive and electronics industries due to their excellent physical and chemical properties. Due to the localized and non-contact process, use of lasers for cutting could result in precise cut with small heat-affected zone (HAZ). Precision laser cutting involving various materials is important in high-volume manufacturing processes to minimize operational cost, error reduction and improve product quality. This study uses grey relational analysis to determine a single optimized set of cutting parameters for three different thermoplastics. The set of the optimized processing parameters is determined based on the highest relational grade and was found at low laser power (200 W), high cutting speed (0.4 m/min) and low compressed air pressure (2.5 bar). The result matches with the objective set in the present study. Analysis of variance (ANOVA) is then carried out to ascertain the relative influence of process parameters on the cutting characteristics. It was found that the laser power has dominant effect on HAZ for all thermoplastics.

On the synergistic use of microwave and infrared satellite observations to monitor soil moisture and flooding

USDA-ARS?s Scientific Manuscript database

Extreme hydrological processes are often very dynamic and destructive.A better understanding of these processes requires an accurate mapping of key variables that control them. In this regard, soil moisture is perhaps the most important parameter that impacts the magnitude of flooding events as it c...

Clinching for sheet materials

PubMed Central

He, Xiaocong

2017-01-01

Abstract Latest developments in the clinching of sheet materials are reviewed in this article. Important issues are discussed, such as tool design, process parameters and joinability of some new lightweight sheet materials. Hybrid and modified clinching processes are introduced to a general reader. Several unaddressed issues in the clinching of sheet materials are identified. PMID:28656065

Laboratory Studies of Heterogeneous Chemical Processes of Atmospheric Importance

NASA Technical Reports Server (NTRS)

Molina, Mario J.

2004-01-01

The objective of this study is to conduct measurements of chemical kinetics parameters for heterogeneous reactions of importance in the stratosphere and the troposphere. It involves the elucidation of the mechanism of the interaction of HCl vapor with ice surfaces, which is the first step in the heterogeneous chlorine activation processes, as well as the investigation of the atmospheric oxidation mechanism of soot particles emitted by biomass and fossil fuels. The techniques being employed include turbulent flow-chemical ionization mass spectrometry and optical ellipsometry, among others.

Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.

Experimental investigation on the spiral trepanning of K24 superalloy with femtosecond laser

NASA Astrophysics Data System (ADS)

Wang, Maolu; Yang, Lijun; Zhang, Shuai; Wang, Yang

2018-05-01

Film cooling holes are crucial for improving the performance of the aviation engine. In the paper, the processing of the film cooling holes on K24 superalloy by femtosecond laser is investigated. By comparing the three different drilling methods, the spiral trepanning method is chosen, and all the drilling experiments are carried out in this way. The experimental results show that the drilling of femtosecond laser pulses has distinct merits against that of the traditional long pulse laser, which can realize the "cold" processing with less recasting layer and less crack. The influence of each process parameter on roundness and taper, which are the important parameters to measure the quality of holes, is analyzed in detail, and the method to decrease it is proposed. To further reduce the recasting layer, the processing quality of the inner wall of the micro hole is investigated by scanning electron microscopy (SEM) equipped with energy disperse spectroscopy (EDS), the mechanism of the femtosecond laser interaction with K24 superalloy is further revealed. The investigation to the film hole machining by femtosecond laser has important practical significance.

Polypropylene Production Optimization in Fluidized Bed Catalytic Reactor (FBCR): Statistical Modeling and Pilot Scale Experimental Validation

PubMed Central

Khan, Mohammad Jakir Hossain; Hussain, Mohd Azlan; Mujtaba, Iqbal Mohammed

2014-01-01

Propylene is one type of plastic that is widely used in our everyday life. This study focuses on the identification and justification of the optimum process parameters for polypropylene production in a novel pilot plant based fluidized bed reactor. This first-of-its-kind statistical modeling with experimental validation for the process parameters of polypropylene production was conducted by applying ANNOVA (Analysis of variance) method to Response Surface Methodology (RSM). Three important process variables i.e., reaction temperature, system pressure and hydrogen percentage were considered as the important input factors for the polypropylene production in the analysis performed. In order to examine the effect of process parameters and their interactions, the ANOVA method was utilized among a range of other statistical diagnostic tools such as the correlation between actual and predicted values, the residuals and predicted response, outlier t plot, 3D response surface and contour analysis plots. The statistical analysis showed that the proposed quadratic model had a good fit with the experimental results. At optimum conditions with temperature of 75°C, system pressure of 25 bar and hydrogen percentage of 2%, the highest polypropylene production obtained is 5.82% per pass. Hence it is concluded that the developed experimental design and proposed model can be successfully employed with over a 95% confidence level for optimum polypropylene production in a fluidized bed catalytic reactor (FBCR). PMID:28788576

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newsom, R. K.; Sivaraman, C.; Shippert, T. R.

Wind speed and direction, together with pressure, temperature, and relative humidity, are the most fundamental atmospheric state parameters. Accurate measurement of these parameters is crucial for numerical weather prediction. Vertically resolved wind measurements in the atmospheric boundary layer are particularly important for modeling pollutant and aerosol transport. Raw data from a scanning coherent Doppler lidar system can be processed to generate accurate height-resolved measurements of wind speed and direction in the atmospheric boundary layer.

Continuous welding of unidirectional fiber reinforced thermoplastic tape material

NASA Astrophysics Data System (ADS)

Schledjewski, Ralf

2017-10-01

Continuous welding techniques like thermoplastic tape placement with in situ consolidation offer several advantages over traditional manufacturing processes like autoclave consolidation, thermoforming, etc. However, still there is a need to solve several important processing issues before it becomes a viable economic process. Intensive process analysis and optimization has been carried out in the past through experimental investigation, model definition and simulation development. Today process simulation is capable to predict resulting consolidation quality. Effects of material imperfections or process parameter variations are well known. But using this knowledge to control the process based on online process monitoring and according adaption of the process parameters is still challenging. Solving inverse problems and using methods for automated code generation allowing fast implementation of algorithms on targets are required. The paper explains the placement technique in general. Process-material-property-relationships and typical material imperfections are described. Furthermore, online monitoring techniques and how to use them for a model based process control system are presented.

Consensus statement with recommendations on active surveillance inclusion criteria and definition of progression in men with localized prostate cancer: the critical role of the pathologist.

PubMed

Montironi, Rodolfo; Hammond, Elizabeth H; Lin, Daniel W; Gore, John L; Srigley, John R; Samaratunga, Hema; Egevad, Lars; Rubin, Mark A; Nacey, John; Klotz, Laurence; Sandler, Howard; Zietman, Anthony L; Holden, Stuart; Humphrey, Peter A; Evans, Andrew J; Delahunt, Brett; McKenney, Jesse K; Berney, Daniel; Wheeler, Thomas M; Chinnaiyan, Arul; True, Lawrence; Knudsen, Beatrice; Epstein, Jonathan I; Amin, Mahul B

2014-12-01

Active surveillance (AS) is an important management option for men with low-risk, clinically localized prostate cancer. The clinical parameters for patient selection and definition of progression for AS protocols are evolving as data from several large cohorts matures. Vital to this process is the critical role pathologic parameters play in identifying appropriate candidates for AS. These findings need to be reproducible and consistently reported by surgical pathologists. This report highlights the importance of accurate pathology reporting as a critical component of these protocols.

Functional relationship-based alarm processing system

DOEpatents

Corsberg, D.R.

1988-04-22

A functional relationship-based alarm processing system and method analyzes each alarm as it is activated and determines its relative importance with other currently activated alarms and signals in accordance with the functional relationships that the newly activated alarm has with other currently activated alarms. Once the initial level of importance of the alarm has been determined, that alarm is again evaluated if another related alarm is activated or deactivated. Thus, each alarm's importance is continuously updated as the state of the process changes during a scenario. Four hierarchical relationships are defined by this alarm filtering methodology: (1) level precursor (usually occurs when there are two alarm settings on the same parameter); (2) direct precursor (based on causal factors between two alarms); (3) required action (system response or action expected within a specified time following activation of an alarm or combination of alarms and process signals); and (4) blocking condition (alarms that are normally expected and are not considered important). The alarm processing system and method is sensitive to the dynamic nature of the process being monitored and is capable of changing the relative importance of each alarm as necessary. 12 figs.

Functional relationship-based alarm processing

DOEpatents

Corsberg, Daniel R.

1988-01-01

A functional relationship-based alarm processing system and method analyzes each alarm as it is activated and determines its relative importance with other currently activated alarms and signals in accordance with the relationships that the newly activated alarm has with other currently activated alarms. Once the initial level of importance of the alarm has been determined, that alarm is again evaluated if another related alarm is activated. Thus, each alarm's importance is continuously oupdated as the state of the process changes during a scenario. Four hierarchical relationships are defined by this alarm filtering methodology: (1) level precursor (usually occurs when there are two alarm settings on the same parameter); (2) direct precursor (based on caussal factors between two alarms); (3) required action (system response or action) expected within a specified time following activation of an alarm or combination of alarms and process signals); and (4) blocking condition (alarms that are normally expected and are not considered important). The alarm processing system and method is sensitive to the dynamic nature of the process being monitored and is capable of changing the relative importance of each alarm as necessary.

Functional relationship-based alarm processing system

DOEpatents

Corsberg, Daniel R.

1989-01-01

A functional relationship-based alarm processing system and method analyzes each alarm as it is activated and determines its relative importance with other currently activated alarms and signals in accordance with the functional relationships that the newly activated alarm has with other currently activated alarms. Once the initial level of importance of the alarm has been determined, that alarm is again evaluated if another related alarm is activated or deactivated. Thus, each alarm's importance is continuously updated as the state of the process changes during a scenario. Four hierarchical relationships are defined by this alarm filtering methodology: (1) level precursor (usually occurs when there are two alarm settings on the same parameter); (2) direct precursor (based on causal factors between two alarms); (3) required action (system response or action expected within a specified time following activation of an alarm or combination of alarms and process signals); and (4) blocking condition (alarms that are normally expected and are not considered important). The alarm processing system and method is sensitive to the dynamic nature of the process being monitored and is capable of changing the relative importance of each alarm as necessary.

MOVES sensitivity study

DOT National Transportation Integrated Search

2012-01-01

Purpose: : To determine ranking of important parameters and the overall sensitivity to values of variables in MOVES : To allow a greater understanding of the MOVES modeling process for users : Continued support by FHWA to transportation modeling comm...

Monitoring the quality of welding based on welding current and ste analysis

NASA Astrophysics Data System (ADS)

Mazlan, Afidatusshimah; Daniyal, Hamdan; Izzani Mohamed, Amir; Ishak, Mahadzir; Hadi, Amran Abdul

2017-10-01

Qualities of welding play an important part in industry especially in manufacturing field. Post-welding non-destructive test is one of the importance process to ensure the quality of welding but it is time consuming and costly. To reduce the chance of defects, online monitoring had been utilized by continuously sense some of welding parameters and predict welding quality. One of the parameters is welding current, which is rich of information but lack of study focus on extract them at signal analysis level. This paper presents the analysis of welding current using Short Time Energy (STE) signal processing to quantify the pattern of the current. GMAW set with carbon steel specimens are used in this experimental study with high-bandwidth and high sampling rate oscilloscope capturing the welding current. The results indicate welding current as signatures have high correlation with the welding process. Continue with STE analysis, the value below 5000 is declare as good welding, meanwhile the STE value more than 6000 is contained defect.

Numerical study on injection parameters optimization of thin wall and biodegradable polymers parts

NASA Astrophysics Data System (ADS)

Santos, C.; Mendes, A.; Carreira, P.; Mateus, A.; Malça, C.

2017-07-01

Nowadays, the molds industry searches new markets, with diversified and added value products. The concept associated to the production of thin walled and biodegradable parts mostly manufactured by injection process has assumed a relevant importance due to environmental and economic factors. The growth of a global consciousness about the harmful effects of the conventional polymers in our life quality associated with the legislation imposed, become key factors for the choice of a particular product by the consumer. The target of this work is to provide an integrated solution for the injection of parts with thin walls and manufactured using biodegradable materials. This integrated solution includes the design and manufacture processes of the mold as well as to find the optimum values for the injection parameters in order to become the process effective and competitive. For this, the Moldflow software was used. It was demonstrated that this computational tool provides an effective responsiveness and it can constitute an important tool in supporting the injection molding of thin-walled and biodegradable parts.

Selecting the Parameters of the Orientation Engine for a Technological Spacecraft

NASA Astrophysics Data System (ADS)

Belousov, A. I.; Sedelnikov, A. V.

2018-01-01

This work provides a solution to the issues of providing favorable conditions for carrying out gravitationally sensitive technological processes on board a spacecraft. It is noted that an important role is played by the optimal choice of the orientation system of the spacecraft and the main parameters of the propulsion system as the most important executive organ of the system of orientation and control of the orbital motion of the spacecraft. Advantages and disadvantages of two different orientation systems are considered. One of them assumes the periodic impulsive inclusion of a low thrust liquid rocket engines, the other is based on the continuous operation of the executing elements. A conclusion is drawn on the need to take into account the composition of gravitationally sensitive processes when choosing the orientation system of the spacecraft.

Functional relationship-based alarm processing

DOEpatents

Corsberg, D.R.

1987-04-13

A functional relationship-based alarm processing system and method analyzes each alarm as it is activated and determines its relative importance with other currently activated alarms and signals in accordance with the relationships that the newly activated alarm has with other currently activated alarms. Once the initial level of importance of the alarm has been determined, that alarm is again evaluated if another related alarm is activated. Thus, each alarm's importance is continuously updated as the state of the process changes during a scenario. Four hierarchical relationships are defined by this alarm filtering methodology: (1) level precursor (usually occurs when there are two alarm settings on the same parameter); (2) direct precursor (based on causal factors between two alarms); (3) required action (system response or action expected within a specified time following activation of an alarm or combination of alarms and process signals); and (4) blocking condition (alarms that are normally expected and are not considered important). 11 figs.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2011-12-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2012-03-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model

NASA Astrophysics Data System (ADS)

Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.

2013-12-01

We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global sensitivity analysis results.

Robust Online Hamiltonian Learning

NASA Astrophysics Data System (ADS)

Granade, Christopher; Ferrie, Christopher; Wiebe, Nathan; Cory, David

2013-05-01

In this talk, we introduce a machine-learning algorithm for the problem of inferring the dynamical parameters of a quantum system, and discuss this algorithm in the example of estimating the precession frequency of a single qubit in a static field. Our algorithm is designed with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online, during experimental data collection, or can be used as a tool for post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. Finally, we discuss the performance of the our algorithm by appeal to the Cramer-Rao bound. This work was financially supported by the Canadian government through NSERC and CERC and by the United States government through DARPA. NW would like to acknowledge funding from USARO-DTO.

Parametric study on single shot peening by dimensional analysis method incorporated with finite element method

NASA Astrophysics Data System (ADS)

Wu, Xian-Qian; Wang, Xi; Wei, Yan-Peng; Song, Hong-Wei; Huang, Chen-Guang

2012-06-01

Shot peening is a widely used surface treatment method by generating compressive residual stress near the surface of metallic materials to increase fatigue life and resistance to corrosion fatigue, cracking, etc. Compressive residual stress and dent profile are important factors to evaluate the effectiveness of shot peening process. In this paper, the influence of dimensionless parameters on maximum compressive residual stress and maximum depth of the dent were investigated. Firstly, dimensionless relations of processing parameters that affect the maximum compressive residual stress and the maximum depth of the dent were deduced by dimensional analysis method. Secondly, the influence of each dimensionless parameter on dimensionless variables was investigated by the finite element method. Furthermore, related empirical formulas were given for each dimensionless parameter based on the simulation results. Finally, comparison was made and good agreement was found between the simulation results and the empirical formula, which shows that a useful approach is provided in this paper for analyzing the influence of each individual parameter.

Soil Erosion as a stochastic process

NASA Astrophysics Data System (ADS)

Casper, Markus C.

2015-04-01

The main tools to provide estimations concerning risk and amount of erosion are different types of soil erosion models: on the one hand, there are empirically based model concepts on the other hand there are more physically based or process based models. However, both types of models have substantial weak points. All empirical model concepts are only capable of providing rough estimates over larger temporal and spatial scales, they do not account for many driving factors that are in the scope of scenario related analysis. In addition, the physically based models contain important empirical parts and hence, the demand for universality and transferability is not given. As a common feature, we find, that all models rely on parameters and input variables, which are to certain, extend spatially and temporally averaged. A central question is whether the apparent heterogeneity of soil properties or the random nature of driving forces needs to be better considered in our modelling concepts. Traditionally, researchers have attempted to remove spatial and temporal variability through homogenization. However, homogenization has been achieved through physical manipulation of the system, or by statistical averaging procedures. The price for obtaining this homogenized (average) model concepts of soils and soil related processes has often been a failure to recognize the profound importance of heterogeneity in many of the properties and processes that we study. Especially soil infiltrability and the resistance (also called "critical shear stress" or "critical stream power") are the most important empirical factors of physically based erosion models. The erosion resistance is theoretically a substrate specific parameter, but in reality, the threshold where soil erosion begins is determined experimentally. The soil infiltrability is often calculated with empirical relationships (e.g. based on grain size distribution). Consequently, to better fit reality, this value needs to be corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.

Volatilisation and competing processes computed for a pesticide applied to plants in a wind tunnel system.

PubMed

Leistra, Minze; Wolters, André; van den Berg, Frederik

2008-06-01

Volatilisation of pesticides from crop canopies can be an important emission pathway. In addition to pesticide properties, competing processes in the canopy and environmental conditions play a part. A computation model is being developed to simulate the processes, but only some of the input data can be obtained directly from the literature. Three well-defined experiments on the volatilisation of radiolabelled parathion-methyl (as example compound) from plants in a wind tunnel system were simulated with the computation model. Missing parameter values were estimated by calibration against the experimental results. The resulting thickness of the air boundary layer, rate of plant penetation and rate of phototransformation were compared with a diversity of literature data. The sequence of importance of the canopy processes was: volatilisation > plant penetration > phototransformation. Computer simulation of wind tunnel experiments, with radiolabelled pesticide sprayed on plants, yields values for the rate coefficients of processes at the plant surface. As some input data for simulations are not required in the framework of registration procedures, attempts to estimate missing parameter values on the basis of divergent experimental results have to be continued. Copyright (c) 2008 Society of Chemical Industry.

Modeling carbon cycle process of soil profile in Loess Plateau of China

NASA Astrophysics Data System (ADS)

Yu, Y.; Finke, P.; Guo, Z.; Wu, H.

2011-12-01

SoilGen2 is a process-based model, which could reconstruct soil formation under various climate conditions, parent materials, vegetation types, slopes, expositions and time scales. Both organic and inorganic carbon cycle processes could be simulated, while the later process is important in carbon cycle of arid and semi-arid regions but seldom being studied. After calibrating parameters of dust deposition rate and segments depth affecting elements transportation and deposition in the profile, modeling results after 10000 years were confronted with measurements of two soil profiles in loess plateau of China, The simulated trends of organic carbon and CaCO3 in the profile are similar to measured values. Relative sensitivity analysis for carbon cycle process have been done and the results show that the change of organic carbon in long time scale is more sensitive to precipitation, temperature, plant carbon input and decomposition parameters (decomposition rate of humus, ratio of CO2/(BIO+HUM), etc.) in the model. As for the inorganic carbon cycle, precipitation and potential evaporation are important for simulation quality, while the leaching and deposition of CaCO3 are not sensitive to pCO2 and temperature of atmosphere.

Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets

PubMed Central

Sun, Fei; Xu, Bing; Zhang, Yi; Dai, Shengyun; Yang, Chan; Cui, Xianglong; Shi, Xinyuan; Qiao, Yanjiang

2016-01-01

The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules’ properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet. PMID:27932865

Toolpath Strategy and Optimum Combination of Machining Parameter during Pocket Mill Process of Plastic Mold Steels Material

NASA Astrophysics Data System (ADS)

Wibowo, Y. T.; Baskoro, S. Y.; Manurung, V. A. T.

2018-02-01

Plastic based products spread all over the world in many aspects of life. The ability to substitute other materials is getting stronger and wider. The use of plastic materials increases and become unavoidable. Plastic based mass production requires injection process as well Mold. The milling process of plastic mold steel material was done using HSS End Mill cutting tool that is widely used in a small and medium enterprise for the reason of its ability to be re sharpened and relatively inexpensive. Study on the effect of the geometry tool states that it has an important effect on the quality improvement. Cutting speed, feed rate, depth of cut and radii are input parameters beside to the tool path strategy. This paper aims to investigate input parameter and cutting tools behaviors within some different tool path strategy. For the reason of experiments efficiency Taguchi method and ANOVA were used. Response studied is surface roughness and cutting behaviors. By achieving the expected quality, no more additional process is required. Finally, the optimal combination of machining parameters will deliver the expected roughness and of course totally reduced cutting time. However actually, SMEs do not optimally use this data for cost reduction.

Optimizing pulsed Nd:YAG laser beam welding process parameters to attain maximum ultimate tensile strength for thin AISI316L sheet using response surface methodology and simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Torabi, Amir; Kolahan, Farhad

2018-07-01

Pulsed laser welding is a powerful technique especially suitable for joining thin sheet metals. In this study, based on experimental data, pulsed laser welding of thin AISI316L austenitic stainless steel sheet has been modeled and optimized. The experimental data required for modeling are gathered as per Central Composite Design matrix in Response Surface Methodology (RSM) with full replication of 31 runs. Ultimate Tensile Strength (UTS) is considered as the main quality measure in laser welding. Furthermore, the important process parameters including peak power, pulse duration, pulse frequency and welding speed are selected as input process parameters. The relation between input parameters and the output response is established via full quadratic response surface regression with confidence level of 95%. The adequacy of the regression model was verified using Analysis of Variance technique results. The main effects of each factor and the interactions effects with other factors were analyzed graphically in contour and surface plot. Next, to maximum joint UTS, the best combinations of parameters levels were specified using RSM. Moreover, the mathematical model is implanted into a Simulated Annealing (SA) optimization algorithm to determine the optimal values of process parameters. The results obtained by both SA and RSM optimization techniques are in good agreement. The optimal parameters settings for peak power of 1800 W, pulse duration of 4.5 ms, frequency of 4.2 Hz and welding speed of 0.5 mm/s would result in a welded joint with 96% of the base metal UTS. Computational results clearly demonstrate that the proposed modeling and optimization procedures perform quite well for pulsed laser welding process.

Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone.

PubMed

Tahmasbi, Vahid; Ghoreishi, Majid; Zolfaghari, Mojtaba

2017-11-01

The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes.

Castor Oil: Properties, Uses, and Optimization of Processing Parameters in Commercial Production

PubMed Central

Patel, Vinay R.; Dumancas, Gerard G.; Kasi Viswanath, Lakshmi C.; Maples, Randall; Subong, Bryan John J.

2016-01-01

Castor oil, produced from castor beans, has long been considered to be of important commercial value primarily for the manufacturing of soaps, lubricants, and coatings, among others. Global castor oil production is concentrated primarily in a small geographic region of Gujarat in Western India. This region is favorable due to its labor-intensive cultivation method and subtropical climate conditions. Entrepreneurs and castor processors in the United States and South America also cultivate castor beans but are faced with the challenge of achieving high castor oil production efficiency, as well as obtaining the desired oil quality. In this manuscript, we provide a detailed analysis of novel processing methods involved in castor oil production. We discuss novel processing methods by explaining specific processing parameters involved in castor oil production. PMID:27656091

Radiation dosimetry for quality control of food preservation and disinfestation

NASA Astrophysics Data System (ADS)

McLaughlin, W. L.; Miller, A.; Uribe, R. M.

In the use of x and gamma rays and scanned electron beams to extend the shelf life of food by delay of sprouting and ripening, killing of microbes, and control of insect population, quality assurance is provided by standardized radiation dosimetry. By strategic placement of calibrated dosimeters that are sufficiently stable and reproducible, it is possible to monitor minimum and maximum radiation absorbed dose levels and dose uniformity for a given processed foodstuff. The dosimetry procedure is especially important in the commisioning of a process and in making adjustments of process parameters (e.g. conveyor speed) to meet changes that occur in product and source parameters (e.g. bulk density and radiation spectrum). Routine dosimetry methods and certain corrections of dosimetry data may be selected for the radiations used in typical food processes.

Castor Oil: Properties, Uses, and Optimization of Processing Parameters in Commercial Production.

PubMed

Patel, Vinay R; Dumancas, Gerard G; Kasi Viswanath, Lakshmi C; Maples, Randall; Subong, Bryan John J

2016-01-01

Castor oil, produced from castor beans, has long been considered to be of important commercial value primarily for the manufacturing of soaps, lubricants, and coatings, among others. Global castor oil production is concentrated primarily in a small geographic region of Gujarat in Western India. This region is favorable due to its labor-intensive cultivation method and subtropical climate conditions. Entrepreneurs and castor processors in the United States and South America also cultivate castor beans but are faced with the challenge of achieving high castor oil production efficiency, as well as obtaining the desired oil quality. In this manuscript, we provide a detailed analysis of novel processing methods involved in castor oil production. We discuss novel processing methods by explaining specific processing parameters involved in castor oil production.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

PubMed

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

PubMed Central

2010-01-01

Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. Results In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. Conclusions The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates. PMID:20500862

Development of process parameters for 22 nm PMOS using 2-D analytical modeling

NASA Astrophysics Data System (ADS)

Maheran, A. H. Afifah; Menon, P. S.; Ahmad, I.; Shaari, S.; Faizah, Z. A. Noor

2015-04-01

The complementary metal-oxide-semiconductor field effect transistor (CMOSFET) has become major challenge to scaling and integration. Innovation in transistor structures and integration of novel materials are necessary to sustain this performance trend. CMOS variability in the scaling technology becoming very important concern due to limitation of process control; over statistically variability related to the fundamental discreteness and materials. Minimizing the transistor variation through technology optimization and ensuring robust product functionality and performance is the major issue.In this article, the continuation study on process parameters variations is extended and delivered thoroughly in order to achieve a minimum leakage current (ILEAK) on PMOS planar transistor at 22 nm gate length. Several device parameters are varies significantly using Taguchi method to predict the optimum combination of process parameters fabrication. A combination of high permittivity material (high-k) and metal gate are utilized accordingly as gate structure where the materials include titanium dioxide (TiO2) and tungsten silicide (WSix). Then the L9 of the Taguchi Orthogonal array is used to analyze the device simulation where the results of signal-to-noise ratio (SNR) of Smaller-the-Better (STB) scheme are studied through the percentage influences of the process parameters. This is to achieve a minimum ILEAK where the maximum predicted ILEAK value by International Technology Roadmap for Semiconductors (ITRS) 2011 is said to should not above 100 nA/µm. Final results shows that the compensation implantation dose acts as the dominant factor with 68.49% contribution in lowering the device's leakage current. The absolute process parameters combination results in ILEAK mean value of 3.96821 nA/µm where is far lower than the predicted value.

Development of process parameters for 22 nm PMOS using 2-D analytical modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maheran, A. H. Afifah; Menon, P. S.; Shaari, S.

2015-04-24

The complementary metal-oxide-semiconductor field effect transistor (CMOSFET) has become major challenge to scaling and integration. Innovation in transistor structures and integration of novel materials are necessary to sustain this performance trend. CMOS variability in the scaling technology becoming very important concern due to limitation of process control; over statistically variability related to the fundamental discreteness and materials. Minimizing the transistor variation through technology optimization and ensuring robust product functionality and performance is the major issue.In this article, the continuation study on process parameters variations is extended and delivered thoroughly in order to achieve a minimum leakage current (I{sub LEAK}) onmore » PMOS planar transistor at 22 nm gate length. Several device parameters are varies significantly using Taguchi method to predict the optimum combination of process parameters fabrication. A combination of high permittivity material (high-k) and metal gate are utilized accordingly as gate structure where the materials include titanium dioxide (TiO{sub 2}) and tungsten silicide (WSi{sub x}). Then the L9 of the Taguchi Orthogonal array is used to analyze the device simulation where the results of signal-to-noise ratio (SNR) of Smaller-the-Better (STB) scheme are studied through the percentage influences of the process parameters. This is to achieve a minimum I{sub LEAK} where the maximum predicted I{sub LEAK} value by International Technology Roadmap for Semiconductors (ITRS) 2011 is said to should not above 100 nA/µm. Final results shows that the compensation implantation dose acts as the dominant factor with 68.49% contribution in lowering the device’s leakage current. The absolute process parameters combination results in I{sub LEAK} mean value of 3.96821 nA/µm where is far lower than the predicted value.« less

Impact of process parameters on the breakage kinetics of poorly water-soluble drugs during wet stirred media milling: a microhydrodynamic view.

PubMed

Afolabi, Afolawemi; Akinlabi, Olakemi; Bilgili, Ecevit

2014-01-23

Wet stirred media milling has proven to be a robust process for producing nanoparticle suspensions of poorly water-soluble drugs. As the process is expensive and energy-intensive, it is important to study the breakage kinetics, which determines the cycle time and production rate for a desired fineness. Although the impact of process parameters on the properties of final product suspensions has been investigated, scant information is available regarding their impact on the breakage kinetics. Here, we elucidate the impact of stirrer speed, bead concentration, and drug loading on the breakage kinetics via a microhydrodynamic model for the bead-bead collisions. Suspensions of griseofulvin, a model poorly water-soluble drug, were prepared in the presence of two stabilizers: hydroxypropyl cellulose and sodium dodecyl sulfate. Laser diffraction, scanning electron microscopy, and rheometry were used to characterize them. Various microhydrodynamic parameters including a newly defined milling intensity factor was calculated. An increase in either the stirrer speed or the bead concentration led to an increase in the specific energy and the milling intensity factor, consequently faster breakage. On the other hand, an increase in the drug loading led to a decrease in these parameters and consequently slower breakage. While all microhydrodynamic parameters provided significant physical insight, only the milling intensity factor was capable of explaining the influence of all parameters directly through its strong correlation with the process time constant. Besides guiding process optimization, the analysis rationalizes the preparation of a single high drug-loaded batch (20% or higher) instead of multiple dilute batches. Copyright © 2013 Elsevier B.V. All rights reserved.

32 CFR 651.48 - Scoping process.

Code of Federal Regulations, 2010 CFR

2010-07-01

... significantly affecting the environment will go through scoping unless extenuating circumstances make it... associated environmental controversy. (4) Importance of the affected environmental parameters. (5... the affected Army organization or installation. Such integration is encouraged. (f) Scoping procedures...

Using Noise and Fluctuations for In Situ Measurements of Nitrogen Diffusion Depth.

PubMed

Samoila, Cornel; Ursutiu, Doru; Schleer, Walter-Harald; Jinga, Vlad; Nascov, Victor

2016-10-05

In manufacturing processes involving diffusion (of C, N, S, etc.), the evolution of the layer depth is of the utmost importance: the success of the entire process depends on this parameter. Currently, nitriding is typically either calibrated using a "post process" method or controlled via indirect measurements (H2, O2, H2O + CO2). In the absence of "in situ" monitoring, any variation in the process parameters (gas concentration, temperature, steel composition, distance between sensors and furnace chamber) can cause expensive process inefficiency or failure. Indirect measurements can prevent process failure, but uncertainties and complications may arise in the relationship between the measured parameters and the actual diffusion process. In this paper, a method based on noise and fluctuation measurements is proposed that offers direct control of the layer depth evolution because the parameters of interest are measured in direct contact with the nitrided steel (represented by the active electrode). The paper addresses two related sets of experiments. The first set of experiments consisted of laboratory tests on nitrided samples using Barkhausen noise and yieded a linear relationship between the frequency exponent in the Hooge equation and the nitriding time. For the second set, a specific sensor based on conductivity noise (at the nitriding temperature) was built for shop-floor experiments. Although two different types of noise were measured in these two sets of experiments, the use of the frequency exponent to monitor the process evolution remained valid.

Membrane tension: A challenging but universal physical parameter in cell biology.

PubMed

Pontes, Bruno; Monzo, Pascale; Gauthier, Nils C

2017-11-01

The plasma membrane separates the interior of cells from the outside environment. The membrane tension, defined as the force per unit length acting on a cross-section of membrane, regulates many vital biological processes. In this review, we summarize the first historical findings and the latest advances, showing membrane tension as an important physical parameter in cell biology. We also discuss how this parameter must be better integrated and we propose experimental approaches for key unanswered questions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biennial Guidance Test Symposium (14th) held in Holloman Air Force Base, New Mexico on 3-5 October 1989. Volume 1

DTIC Science & Technology

1989-10-30

assembled pair is tumble lapped. Tumble lapping is a process in which Mechanically, the 1.5-inch diameter rotors a a weighted lapping element and slurry of...parameter met AGTF requirements at that site. Weighting factors were than assigned to each parameter as an indication of importance of the parameter to...AGTF. The weighted score was determined by multiplying the score by the weighting factor. The weighted scores were then totaled for each site to

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

Adsorptive removal of aniline by granular activated carbon from aqueous solutions with catechol and resorcinol.

PubMed

Suresh, S; Srivastava, V C; Mishrab, I M

2012-01-01

In the present paper, the removal of aniline by adsorption process onto granular activated carbon (GAC) is reported from aqueous solutions containing catechol and resorcinol separately. The Taguchi experimental design was applied to study the effect of such parameters as the initial component concentrations (C(0,i)) of two solutes (aniline and catechol or aniline and resorcinol) in the solution, temperature (T), adsorbent dosage (m) and contact time (t). The L27 orthogonal array consisting of five parameters each with three levels was used to determine the total amount of solutes adsorbed on GAC (q(tot), mmol/g) and the signal-to-noise ratio. The analysis of variance (ANOVA) was used to determine the optimum conditions. Under these conditions, the ANOVA shows that m is the most important parameter in the adsorption process. The most favourable levels of process parameters were T = 303 K, m = 10 g/l and t = 660 min for both the systems, qtot values in the confirmation experiments carried out at optimum conditions were 0.73 and 0.95 mmol/g for aniline-catechol and aniline-resorcinol systems, respectively.

Standardization of domestic frying processes by an engineering approach.

PubMed

Franke, K; Strijowski, U

2011-05-01

An approach was developed to enable a better standardization of domestic frying of potato products. For this purpose, 5 domestic fryers differing in heating power and oil capacity were used. A very defined frying process using a highly standardized model product and a broad range of frying conditions was carried out in these fryers and the development of browning representing an important quality parameter was measured. Product-to-oil ratio, oil temperature, and frying time were varied. Quite different color changes were measured in the different fryers although the same frying process parameters were applied. The specific energy consumption for water evaporation (spECWE) during frying related to product amount was determined for all frying processes to define an engineering parameter for characterizing the frying process. A quasi-linear regression approach was applied to calculate this parameter from frying process settings and fryer properties. The high significance of the regression coefficients and a coefficient of determination close to unity confirmed the suitability of this approach. Based on this regression equation, curves for standard frying conditions (SFC curves) were calculated which describe the frying conditions required to obtain the same level of spECWE in the different domestic fryers. Comparison of browning results from the different fryers operated at conditions near the SFC curves confirmed the applicability of the approach. © 2011 Institute of Food Technologists®

Application of Fourier transform near-infrared spectroscopy to optimization of green tea steaming process conditions.

PubMed

Ono, Daiki; Bamba, Takeshi; Oku, Yuichi; Yonetani, Tsutomu; Fukusaki, Eiichiro

2011-09-01

In this study, we constructed prediction models by metabolic fingerprinting of fresh green tea leaves using Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression analysis to objectively optimize of the steaming process conditions in green tea manufacture. The steaming process is the most important step for manufacturing high quality green tea products. However, the parameter setting of the steamer is currently determined subjectively by the manufacturer. Therefore, a simple and robust system that can be used to objectively set the steaming process parameters is necessary. We focused on FT-NIR spectroscopy because of its simple operation, quick measurement, and low running costs. After removal of noise in the spectral data by principal component analysis (PCA), PLS regression analysis was performed using spectral information as independent variables, and the steaming parameters set by experienced manufacturers as dependent variables. The prediction models were successfully constructed with satisfactory accuracy. Moreover, the results of the demonstrated experiment suggested that the green tea steaming process parameters could be predicted on a larger manufacturing scale. This technique will contribute to improvement of the quality and productivity of green tea because it can objectively optimize the complicated green tea steaming process and will be suitable for practical use in green tea manufacture. Copyright © 2011 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Advanced image processing approach for ET estimation with remote sensing data of varying spectral, spatial and temporal resolutions

Treesearch

Sudhanshu Panda; Devendra Amatya; Young Kim; Ge Sun

2016-01-01

Evapotranspiration (ET) is one of the most important hydrologic parameters for vegetation growth, carbon sequestration, and other associated biodiversity study and analysis. Plant stomatal conductance, leaf area index, canopy temperature, soil moisture, and wind speed values generally correlate well with ET. It is difficult to estimate these hydrologic parameters of...

The development of machine technology processing for earth resource survey

NASA Technical Reports Server (NTRS)

Landgrebe, D. A.

1970-01-01

The following technologies are considered for automatic processing of earth resources data: (1) registration of multispectral and multitemporal images, (2) digital image display systems, (3) data system parameter effects on satellite remote sensing systems, and (4) data compression techniques based on spectral redundancy. The importance of proper spectral band and compression algorithm selections is pointed out.

Constraints on the ^22Ne(α,n)^25Mg reaction rate from ^natMg+n Total and ^25Mg(n,γ ) Cross Sections

NASA Astrophysics Data System (ADS)

Koehler, Paul

2002-10-01

The ^22Ne(α,n)^25Mg reaction is the neutron source during the s process in massive and intermediate mass stars as well as a secondary neutron source during the s process in low mass stars. Therefore, an accurate determination of this rate is important for a better understanding of the origin of nuclides heavier than iron as well as for improving s-process models. Also, because the s process produces seed nuclides for a later p process in massive stars, an accurate value for this rate is important for a better understanding of the p process. Because the lowest observed resonance in direct ^22Ne(α,n)^25Mg measurements is considerably above the most important energy range for s-process temperatures, the uncertainty in this rate is dominated by the poorly known properties of states in ^26Mg between this resonance and threshold. Neutron measurements can observe these states with much better sensitivity and determine their parameters much more accurately than direct ^22Ne(α,n)^25Mg measurements. I have analyzed previously reported Mg+n total and ^25Mg(n,γ ) cross sections to obtain a much improved set of resonance parameters for states in ^26Mg in this region, and an improved estimate of the uncertainty in the ^22Ne(α,n)^25Mg reaction rate. This work was supported by the U.S. DOE under contract No. DE-AC05-00OR22725 with UT-Battell, LLC.

Sensitivity analysis of add-on price estimate for select silicon wafering technologies

NASA Technical Reports Server (NTRS)

Mokashi, A. R.

1982-01-01

The cost of producing wafers from silicon ingots is a major component of the add-on price of silicon sheet. Economic analyses of the add-on price estimates and their sensitivity internal-diameter (ID) sawing, multiblade slurry (MBS) sawing and fixed-abrasive slicing technique (FAST) are presented. Interim price estimation guidelines (IPEG) are used for estimating a process add-on price. Sensitivity analysis of price is performed with respect to cost parameters such as equipment, space, direct labor, materials (blade life) and utilities, and the production parameters such as slicing rate, slices per centimeter and process yield, using a computer program specifically developed to do sensitivity analysis with IPEG. The results aid in identifying the important cost parameters and assist in deciding the direction of technology development efforts.

Resist Parameter Extraction from Line-and-Space Patterns of Chemically Amplified Resist for Extreme Ultraviolet Lithography

NASA Astrophysics Data System (ADS)

Kozawa, Takahiro; Oizumi, Hiroaki; Itani, Toshiro; Tagawa, Seiichi

2010-11-01

The development of extreme ultraviolet (EUV) lithography has progressed owing to worldwide effort. As the development status of EUV lithography approaches the requirements for the high-volume production of semiconductor devices with a minimum line width of 22 nm, the extraction of resist parameters becomes increasingly important from the viewpoints of the accurate evaluation of resist materials for resist screening and the accurate process simulation for process and mask designs. In this study, we demonstrated that resist parameters (namely, quencher concentration, acid diffusion constant, proportionality constant of line edge roughness, and dissolution point) can be extracted from the scanning electron microscopy (SEM) images of patterned resists without the knowledge on the details of resist contents using two types of latest EUV resist.

Fundamentals of cutting.

PubMed

Williams, J G; Patel, Y

2016-06-06

The process of cutting is analysed in fracture mechanics terms with a view to quantifying the various parameters involved. The model used is that of orthogonal cutting with a wedge removing a layer of material or chip. The behaviour of the chip is governed by its thickness and for large radii of curvature the chip is elastic and smooth cutting occurs. For smaller thicknesses, there is a transition, first to plastic bending and then to plastic shear for small thicknesses and smooth chips are formed. The governing parameters are tool geometry, which is principally the wedge angle, and the material properties of elastic modulus, yield stress and fracture toughness. Friction can also be important. It is demonstrated that the cutting process may be quantified via these parameters, which could be useful in the study of cutting in biology.

The dimensional reduction method for identification of parameters that trade-off due to similar model roles.

PubMed

Davidson, Shaun M; Docherty, Paul D; Murray, Rua

2017-03-01

Parameter identification is an important and widely used process across the field of biomedical engineering. However, it is susceptible to a number of potential difficulties, such as parameter trade-off, causing premature convergence at non-optimal parameter values. The proposed Dimensional Reduction Method (DRM) addresses this issue by iteratively reducing the dimension of hyperplanes where trade off occurs, and running subsequent identification processes within these hyperplanes. The DRM was validated using clinical data to optimize 4 parameters of the widely used Bergman Minimal Model of glucose and insulin kinetics, as well as in-silico data to optimize 5 parameters of the Pulmonary Recruitment (PR) Model. Results were compared with the popular Levenberg-Marquardt (LMQ) Algorithm using a Monte-Carlo methodology, with both methods afforded equivalent computational resources. The DRM converged to a lower or equal residual value in all tests run using the Bergman Minimal Model and actual patient data. For the PR model, the DRM attained significantly lower overall median parameter error values and lower residuals in the vast majority of tests. This shows the DRM has potential to provide better resolution of optimum parameter values for the variety of biomedical models in which significant levels of parameter trade-off occur. Copyright © 2017 Elsevier Inc. All rights reserved.

The Taguchi Method Application to Improve the Quality of a Sustainable Process

NASA Astrophysics Data System (ADS)

Titu, A. M.; Sandu, A. V.; Pop, A. B.; Titu, S.; Ciungu, T. C.

2018-06-01

Taguchi’s method has always been a method used to improve the quality of the analyzed processes and products. This research shows an unusual situation, namely the modeling of some parameters, considered technical parameters, in a process that is wanted to be durable by improving the quality process and by ensuring quality using an experimental research method. Modern experimental techniques can be applied in any field and this study reflects the benefits of interacting between the agriculture sustainability principles and the Taguchi’s Method application. The experimental method used in this practical study consists of combining engineering techniques with experimental statistical modeling to achieve rapid improvement of quality costs, in fact seeking optimization at the level of existing processes and the main technical parameters. The paper is actually a purely technical research that promotes a technical experiment using the Taguchi method, considered to be an effective method since it allows for rapid achievement of 70 to 90% of the desired optimization of the technical parameters. The missing 10 to 30 percent can be obtained with one or two complementary experiments, limited to 2 to 4 technical parameters that are considered to be the most influential. Applying the Taguchi’s Method in the technique and not only, allowed the simultaneous study in the same experiment of the influence factors considered to be the most important in different combinations and, at the same time, determining each factor contribution.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody–peptide fusion

PubMed Central

Goldrick, Stephen; Holmes, William; Bond, Nicholas J.; Lewis, Gareth; Kuiper, Marcel; Turner, Richard

2017-01-01

ABSTRACT Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. PMID:28500668

Determination of optimal tool parameters for hot mandrel bending of pipe elbows

NASA Astrophysics Data System (ADS)

Tabakajew, Dmitri; Homberg, Werner

2018-05-01

Seamless pipe elbows are important components in mechanical, plant and apparatus engineering. Typically, they are produced by the so-called `Hamburg process'. In this hot forming process, the initial pipes are subsequently pushed over an ox-horn-shaped bending mandrel. The geometric shape of the mandrel influences the diameter, bending radius and wall thickness distribution of the pipe elbow. This paper presents the numerical simulation model of the hot mandrel bending process created to ensure that the optimum mandrel geometry can be determined at an early stage. A fundamental analysis was conducted to determine the influence of significant parameters on the pipe elbow quality. The chosen methods and approach as well as the corresponding results are described in this paper.

Health Monitoring and Management for Manufacturing Workers in Adverse Working Conditions.

PubMed

Xu, Xiaoya; Zhong, Miao; Wan, Jiafu; Yi, Minglun; Gao, Tiancheng

2016-10-01

In adverse working conditions, environmental parameters such as metallic dust, noise, and environmental temperature, directly affect the health condition of manufacturing workers. It is therefore important to implement health monitoring and management based on important physiological parameters (e.g., heart rate, blood pressure, and body temperature). In recent years, new technologies, such as body area networks, cloud computing, and smart clothing, have allowed the improvement of the quality of services. In this article, we first give five-layer architecture for health monitoring and management of manufacturing workers. Then, we analyze the system implementation process, including environmental data processing, physical condition monitoring and system services and management, and present the corresponding algorithms. Finally, we carry out an evaluation and analysis from the perspective of insurance and compensation for manufacturing workers in adverse working conditions. The proposed scheme will contribute to the improvement of workplace conditions, realize health monitoring and management, and protect the interests of manufacturing workers.

Poplar response to cadmium and lead soil contamination.

PubMed

Radojčić Redovniković, Ivana; De Marco, Alessandra; Proietti, Chiara; Hanousek, Karla; Sedak, Marija; Bilandžić, Nina; Jakovljević, Tamara

2017-10-01

An outdoor pot experiment was designed to study the potential of poplar (Populus nigra 'Italica') in phytoremediation of cadmium (Cd) and lead (Pb). Poplar was treated with a combination of different concentrations of Cd (w = 10, 25, 50mgkg -1 soil) and Pb (400, 800, 1200mgkg -1 soil) and several physiological and biochemical parameters were monitored including the accumulation and distribution of metals in different plant parts (leaf, stem, root). Simultaneously, the changes in the antioxidant system in roots and leaves were monitored to be able to follow synergistic effects of both heavy metals. Moreover, a statistical analysis based on the Random Forests Analysis (RFA) was performed in order to determine the most important predictors affecting growth and antioxidative machinery activities of poplar under heavy metal stress. The study demonstrated that tested poplar could be a good candidate for phytoextraction processes of Cd in moderately contaminated soils, while in heavily contaminated soil it could be only considered as a phytostabilisator. For Pb remediation only phytostabilisation process could be considered. By using RFA we pointed out that it is important to conduct the experiments in an outdoor space and include environmental conditions in order to study more realistic changes of growth parameters and accumulation and distribution of heavy metals. Also, to be able to better understand the interactions among previously mentioned parameters, it is important to conduct the experiments during prolonged time exposure., This is especially important for the long life cycle woody species. Copyright © 2017. Published by Elsevier Inc.

How important is vehicle safety in the new vehicle purchase process?

PubMed

Koppel, Sjaanie; Charlton, Judith; Fildes, Brian; Fitzharris, Michael

2008-05-01

Whilst there has been a significant increase in the amount of consumer interest in the safety performance of privately owned vehicles, the role that it plays in consumers' purchase decisions is poorly understood. The aims of the current study were to determine: how important vehicle safety is in the new vehicle purchase process; what importance consumers place on safety options/features relative to other convenience and comfort features, and how consumers conceptualise vehicle safety. In addition, the study aimed to investigate the key parameters associated with ranking 'vehicle safety' as the most important consideration in the new vehicle purchase. Participants recruited in Sweden and Spain completed a questionnaire about their new vehicle purchase. The findings from the questionnaire indicated that participants ranked safety-related factors (e.g., EuroNCAP (or other) safety ratings) as more important in the new vehicle purchase process than other vehicle factors (e.g., price, reliability etc.). Similarly, participants ranked safety-related features (e.g., advanced braking systems, front passenger airbags etc.) as more important than non-safety-related features (e.g., route navigation systems, air-conditioning etc.). Consistent with previous research, most participants equated vehicle safety with the presence of specific vehicle safety features or technologies rather than vehicle crash safety/test results or crashworthiness. The key parameters associated with ranking 'vehicle safety' as the most important consideration in the new vehicle purchase were: use of EuroNCAP, gender and education level, age, drivers' concern about crash involvement, first vehicle purchase, annual driving distance, person for whom the vehicle was purchased, and traffic infringement history. The findings from this study are important for policy makers, manufacturers and other stakeholders to assist in setting priorities with regard to the promotion and publicity of vehicle safety features for particular consumer groups (such as younger consumers) in order to increase their knowledge regarding vehicle safety and to encourage them to place highest priority on safety in the new vehicle purchase process.

Using Noise and Fluctuations for In Situ Measurements of Nitrogen Diffusion Depth

PubMed Central

Samoila, Cornel; Ursutiu, Doru; Schleer, Walter-Harald; Jinga, Vlad; Nascov, Victor

2016-01-01

In manufacturing processes involving diffusion (of C, N, S, etc.), the evolution of the layer depth is of the utmost importance: the success of the entire process depends on this parameter. Currently, nitriding is typically either calibrated using a “post process” method or controlled via indirect measurements (H2, O2, H2O + CO2). In the absence of “in situ” monitoring, any variation in the process parameters (gas concentration, temperature, steel composition, distance between sensors and furnace chamber) can cause expensive process inefficiency or failure. Indirect measurements can prevent process failure, but uncertainties and complications may arise in the relationship between the measured parameters and the actual diffusion process. In this paper, a method based on noise and fluctuation measurements is proposed that offers direct control of the layer depth evolution because the parameters of interest are measured in direct contact with the nitrided steel (represented by the active electrode). The paper addresses two related sets of experiments. The first set of experiments consisted of laboratory tests on nitrided samples using Barkhausen noise and yielded a linear relationship between the frequency exponent in the Hooge equation and the nitriding time. For the second set, a specific sensor based on conductivity noise (at the nitriding temperature) was built for shop-floor experiments. Although two different types of noise were measured in these two sets of experiments, the use of the frequency exponent to monitor the process evolution remained valid. PMID:28773941

Process-oriented Observational Metrics for CMIP6 Climate Model Assessments

NASA Astrophysics Data System (ADS)

Jiang, J. H.; Su, H.

2016-12-01

Observational metrics based on satellite observations have been developed and effectively applied during post-CMIP5 model evaluation and improvement projects. As new physics and parameterizations continue to be included in models for the upcoming CMIP6, it is important to continue objective comparisons between observations and model results. This talk will summarize the process-oriented observational metrics and methodologies for constraining climate models with A-Train satellite observations and support CMIP6 model assessments. We target parameters and processes related to atmospheric clouds and water vapor, which are critically important for Earth's radiative budget, climate feedbacks, and water and energy cycles, and thus reduce uncertainties in climate models.

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.

2015-12-01

The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.

Improved silicon nitride for advanced heat engines

NASA Technical Reports Server (NTRS)

Yeh, H. C.; Wimmer, J. M.

1986-01-01

Silicon nitride is a high temperature material currently under consideration for heat engine and other applications. The objective is to improve the net shape fabrication technology of Si3N4 by injection molding. This is to be accomplished by optimizing the process through a series of statistically designed matrix experiments. To provide input to the matrix experiments, a wide range of alternate materials and processing parameters was investigated throughout the whole program. The improvement in the processing is to be demonstrated by a 20 percent increase in strength and a 100 percent increase in the Weibull modulus over that of the baseline material. A full characterization of the baseline process was completed. Material properties were found to be highly dependent on each step of the process. Several important parameters identified thus far are the starting raw materials, sinter/hot isostatic pressing cycle, powder bed, mixing methods, and sintering aid levels.

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

PubMed

Markiewicz, Łukasz; Kubińska, Elżbieta

2015-01-01

This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters. Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology. Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of hot tasks inhibits correct information processing, probably because it is difficult to engage Type 2 processes in such circumstances. Individuals' Type 2 processing abilities (measured by the CRT) assist greater use of information in cold tasks but do not help in hot tasks.

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

PubMed Central

Markiewicz, Łukasz; Kubińska, Elżbieta

2015-01-01

Objective: This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters. Methods: Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology. Results: Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of hot tasks inhibits correct information processing, probably because it is difficult to engage Type 2 processes in such circumstances. Individuals' Type 2 processing abilities (measured by the CRT) assist greater use of information in cold tasks but do not help in hot tasks. PMID:26635652

Parameter extraction with neural networks

NASA Astrophysics Data System (ADS)

Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

1998-06-01

In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs with desired characteristics. Using this method, we can extract optimum values for the parameters and determine the process latitude very quickly.

A Comparison of Full and Empirical Bayes Techniques for Inferring Sea Level Changes from Tide Gauge Records

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Tingley, M.

2016-12-01

Sea level observations from coastal tide gauges are some of the longest instrumental records of the ocean. However, these data can be noisy, biased, and gappy, featuring missing values, and reflecting land motion and local effects. Coping with these issues in a formal manner is a challenging task. Some studies use Bayesian approaches to estimate sea level from tide gauge records, making inference probabilistically. Such methods are typically empirically Bayesian in nature: model parameters are treated as known and assigned point values. But, in reality, parameters are not perfectly known. Empirical Bayes methods thus neglect a potentially important source of uncertainty, and so may overestimate the precision (i.e., underestimate the uncertainty) of sea level estimates. We consider whether empirical Bayes methods underestimate uncertainty in sea level from tide gauge data, comparing to a full Bayes method that treats parameters as unknowns to be solved for along with the sea level field. We develop a hierarchical algorithm that we apply to tide gauge data on the North American northeast coast over 1893-2015. The algorithm is run in full Bayes mode, solving for the sea level process and parameters, and in empirical mode, solving only for the process using fixed parameter values. Error bars on sea level from the empirical method are smaller than from the full Bayes method, and the relative discrepancies increase with time; the 95% credible interval on sea level values from the empirical Bayes method in 1910 and 2010 is 23% and 56% narrower, respectively, than from the full Bayes approach. To evaluate the representativeness of the credible intervals, empirical Bayes and full Bayes methods are applied to corrupted data of a known surrogate field. Using rank histograms to evaluate the solutions, we find that the full Bayes method produces generally reliable error bars, whereas the empirical Bayes method gives too-narrow error bars, such that the 90% credible interval only encompasses 70% of true process values. Results demonstrate that parameter uncertainty is an important source of process uncertainty, and advocate for the fully Bayesian treatment of tide gauge records in ocean circulation and climate studies.

Advanced Method to Estimate Fuel Slosh Simulation Parameters

NASA Technical Reports Server (NTRS)

Schlee, Keith; Gangadharan, Sathya; Ristow, James; Sudermann, James; Walker, Charles; Hubert, Carl

2005-01-01

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the estimation approach to a simple, accurately modeled system, its effectiveness and accuracy can be evaluated. The same experimental setup can then be used with fluid-filled tanks to further evaluate the effectiveness of the process. Ultimately, the proven process can be applied to the full-sized spinning experimental setup to quickly and accurately determine the slosh model parameters for a particular spacecraft mission. Automating the parameter identification process will save time, allow more changes to be made to proposed designs, and lower the cost in the initial design stages.

Beam parameter optimization at CLIC using the process e+e- → HZ → Hq q bar at 380 GeV

NASA Astrophysics Data System (ADS)

Andrianala, F.; Raboanary, R.; Roloff, P.; Schulte, D.

2017-01-01

At CLIC and the ILC beam-beam forces lead to the emission of beamstrahlung photons and a reduction of the effective center-of-mass energy. This degradation is controlled by the choice of the horizontal beam size. A reduction of this parameter would increase the luminosity but also the beamstrahlung. In this paper the optimum choice for the horizontal beam size is investigated for one of the most important physics processes. The Higgsstrahlung process e+e- → HZ is identified in a model-independent manner by observing the Z boson and determining the mass against which it is recoiling. The physics analysis for this process is performed for constant running times, assuming different beam size and taking into account the resulting levels of integrated luminosity and the associated luminosity spectra.

The time-lapse AVO difference inversion for changes in reservoir parameters

NASA Astrophysics Data System (ADS)

Longxiao, Zhi; Hanming, Gu; Yan, Li

2016-12-01

The result of conventional time-lapse seismic processing is the difference between the amplitude and the post-stack seismic data. Although stack processing can improve the signal-to-noise ratio (SNR) of seismic data, it also causes a considerable loss of important information about the amplitude changes and only gives the qualitative interpretation. To predict the changes in reservoir fluid more precisely and accurately, we also need the quantitative information of the reservoir. To achieve this aim, we develop the method of time-lapse AVO (amplitude versus offset) difference inversion. For the inversion of reservoir changes in elastic parameters, we apply the Gardner equation as the constraint and convert the three-parameter inversion of elastic parameter changes into a two-parameter inversion to make the inversion more stable. For the inversion of variations in the reservoir parameters, we infer the relation between the difference of the reflection coefficient and variations in the reservoir parameters, and then invert reservoir parameter changes directly. The results of the theoretical modeling computation and practical application show that our method can estimate the relative variations in reservoir density, P-wave and S-wave velocity, calculate reservoir changes in water saturation and effective pressure accurately, and then provide reference for the rational exploitation of the reservoir.

WORKSHOP ON MONITORING OXIDATION-REDUCTION PROCESSES FOR GROUND-WATER RESTORATION

EPA Science Inventory

Redox conditions are among the most important parameters for controlling contaminant transport and fate in ground-water systems. Oxidation-reduction (redox) reactions mediate the chemical behavior of both inorganic and organic chemical constituents by affecting solubility, rea...

Parameterization guidelines and considerations for hydrologic models

Treesearch

 R. W. Malone; G. Yagow; C. Baffaut; M.W  Gitau; Z. Qi; Devendra Amatya; P.B.   Parajuli; J.V. Bonta; T.R.  Green

2015-01-01

 Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential...

Analyzing the effect of cutting parameters on surface roughness and tool wear when machining nickel based hastelloy - 276

NASA Astrophysics Data System (ADS)

Khidhir, Basim A.; Mohamed, Bashir

2011-02-01

Machining parameters has an important factor on tool wear and surface finish, for that the manufacturers need to obtain optimal operating parameters with a minimum set of experiments as well as minimizing the simulations in order to reduce machining set up costs. The cutting speed is one of the most important cutting parameter to evaluate, it clearly most influences on one hand, tool life, tool stability, and cutting process quality, and on the other hand controls production flow. Due to more demanding manufacturing systems, the requirements for reliable technological information have increased. For a reliable analysis in cutting, the cutting zone (tip insert-workpiece-chip system) as the mechanics of cutting in this area are very complicated, the chip is formed in the shear plane (entrance the shear zone) and is shape in the sliding plane. The temperature contributed in the primary shear, chamfer and sticking, sliding zones are expressed as a function of unknown shear angle on the rake face and temperature modified flow stress in each zone. The experiments were carried out on a CNC lathe and surface finish and tool tip wear are measured in process. Machining experiments are conducted. Reasonable agreement is observed under turning with high depth of cut. Results of this research help to guide the design of new cutting tool materials and the studies on evaluation of machining parameters to further advance the productivity of nickel based alloy Hastelloy - 276 machining.

Analyzing the Effect of Spinning Process Variables on Draw Frame Blended Cotton Mélange Yarn Quality

NASA Astrophysics Data System (ADS)

Ray, Suchibrata; Ghosh, Anindya; Banerjee, Debamalya

2018-06-01

An investigation has been made to study the effect of important spinning process variables namely shade depth, ring frame spindle speed and yarn twist multiplier (TM) on various yarn quality parameters like unevenness, strength, imperfection, elongation at break and hairiness index of draw frame blended cotton mélange yarn. Three factors Box and Behnken design of experiment has been used to conduct the study. The quadratic regression model is used to device the statistical inferences about sensitivity of the yarn quality parameters to the different process variables. The response surfaces are constructed for depicting the geometric representation of yarn quality parameters plotted as a function of process variables. Analysis of the results show that yarn strength of draw frame blended cotton mélange yarn is significantly affected by shade depth and TM. Yarn unevenness is affected by shade depth and ring frame spindle speed. Yarn imperfection level is mainly influenced by the shade depth and spindle speed. The shade depth and yarn TM have shown significant impact on yarn hairiness index.

Analyzing the Effect of Spinning Process Variables on Draw Frame Blended Cotton Mélange Yarn Quality

NASA Astrophysics Data System (ADS)

Ray, Suchibrata; Ghosh, Anindya; Banerjee, Debamalya

2017-12-01

An investigation has been made to study the effect of important spinning process variables namely shade depth, ring frame spindle speed and yarn twist multiplier (TM) on various yarn quality parameters like unevenness, strength, imperfection, elongation at break and hairiness index of draw frame blended cotton mélange yarn. Three factors Box and Behnken design of experiment has been used to conduct the study. The quadratic regression model is used to device the statistical inferences about sensitivity of the yarn quality parameters to the different process variables. The response surfaces are constructed for depicting the geometric representation of yarn quality parameters plotted as a function of process variables. Analysis of the results show that yarn strength of draw frame blended cotton mélange yarn is significantly affected by shade depth and TM. Yarn unevenness is affected by shade depth and ring frame spindle speed. Yarn imperfection level is mainly influenced by the shade depth and spindle speed. The shade depth and yarn TM have shown significant impact on yarn hairiness index.

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation

PubMed Central

Palma Orozco, Rosaura

2018-01-01

Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe the signal behavior. Thus, great importance should be taken to feature extraction which is complicated for the Parameter Estimation (PE)–System Identification (SI) process. When based on an average approximation, nonstationary characteristics are presented. For PE the comparison of three forms of iterative-recursive uses of the Exponential Forgetting Factor (EFF) combined with a linear function to identify a synthetic stochastic signal is presented. The one with best results seen through the functional error is applied to approximate an EEG signal for a simple classification example, showing the effectiveness of our proposal. PMID:29568310

Does the cation really matter? The effect of modifying an ionic liquid cation on an SN2 process.

PubMed

Tanner, Eden E L; Yau, Hon Man; Hawker, Rebecca R; Croft, Anna K; Harper, Jason B

2013-09-28

The rate of reaction of a Menschutkin process in a range of ionic liquids with different cations was investigated, with temperature-dependent kinetic data giving access to activation parameters for the process in each solvent. These data, along with molecular dynamics simulations, demonstrate the importance of accessibility of the charged centre on the cation and that the key interactions are of a generalised electrostatic nature.

Atmospheric corrections for satellite water quality studies

NASA Technical Reports Server (NTRS)

Piech, K. R.; Schott, J. R.

1975-01-01

Variations in the relative value of the blue and green reflectances of a lake can be correlated with important optical and biological parameters measured from surface vessels. Measurement of the relative reflectance values from color film imagery requires removal of atmospheric effects. Data processing is particularly crucial because: (1) lakes are the darkest objects in a scene; (2) minor reflectance changes can correspond to important physical changes; (3) lake systems extend over broad areas in which atmospheric conditions may fluctuate; (4) seasonal changes are of importance; and, (5) effects of weather are important, precluding flights under only ideal weather conditions. Data processing can be accomplished through microdensitometry of scene shadow areas. Measurements of reflectance ratios can be made to an accuracy of plus or minus 12%, sufficient to permit monitoring of important eutrophication indices.

Effective Parameters in Axial Injection Suspension Plasma Spray Process of Alumina-Zirconia Ceramics

NASA Astrophysics Data System (ADS)

Tarasi, F.; Medraj, M.; Dolatabadi, A.; Oberste-Berghaus, J.; Moreau, C.

2008-12-01

Suspension plasma spray (SPS) is a novel process for producing nano-structured coatings with metastable phases using significantly smaller particles as compared to conventional thermal spraying. Considering the complexity of the system there is an extensive need to better understand the relationship between plasma spray conditions and resulting coating microstructure and defects. In this study, an alumina/8 wt.% yttria-stabilized zirconia was deposited by axial injection SPS process. The effects of principal deposition parameters on the microstructural features are evaluated using the Taguchi design of experiment. The microstructural features include microcracks, porosities, and deposition rate. To better understand the role of the spray parameters, in-flight particle characteristics, i.e., temperature and velocity were also measured. The role of the porosity in this multicomponent structure is studied as well. The results indicate that thermal diffusivity of the coatings, an important property for potential thermal barrier applications, is barely affected by the changes in porosity content.

Parameter and Process Significance in Mechanistic Modeling of Cellulose Hydrolysis

NASA Astrophysics Data System (ADS)

Rotter, B.; Barry, A.; Gerhard, J.; Small, J.; Tahar, B.

2005-12-01

The rate of cellulose hydrolysis, and of associated microbial processes, is important in determining the stability of landfills and their potential impact on the environment, as well as associated time scales. To permit further exploration in this field, a process-based model of cellulose hydrolysis was developed. The model, which is relevant to both landfill and anaerobic digesters, includes a novel approach to biomass transfer between a cellulose-bound biofilm and biomass in the surrounding liquid. Model results highlight the significance of the bacterial colonization of cellulose particles by attachment through contact in solution. Simulations revealed that enhanced colonization, and therefore cellulose degradation, was associated with reduced cellulose particle size, higher biomass populations in solution, and increased cellulose-binding ability of the biomass. A sensitivity analysis of the system parameters revealed different sensitivities to model parameters for a typical landfill scenario versus that for an anaerobic digester. The results indicate that relative surface area of cellulose and proximity of hydrolyzing bacteria are key factors determining the cellulose degradation rate.

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

PubMed Central

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale. PMID:22399948

Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

PubMed

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Mangrove Crab Ucides cordatus Removal Does Not Affect Sediment Parameters and Stipule Production in a One Year Experiment in Northern Brazil

PubMed Central

2016-01-01

Mangrove crabs influence ecosystem processes through bioturbation and/or litter feeding. In Brazilian mangroves, the abundant and commercially important crab Ucides cordatus is the main faunal modifier of microtopography establishing up to 2 m deep burrows. They process more than 70% of the leaf litter and propagule production, thus promoting microbial degradation of detritus and benefiting microbe-feeding fiddler crabs. The accelerated nutrient turn-over and increased sediment oxygenation mediated by U. cordatus may enhance mangrove tree growth. Such positive feed-back loop was tested in North Brazil through a one year crab removal experiment simulating increased harvesting rates in a mature Rhizophora mangle forest. Investigated response parameters were sediment salinity, organic matter content, CO2 efflux rates of the surface sediment, and reduction potential. We also determined stipule fall of the mangrove tree R. mangle as a proxy for tree growth. Three treatments were applied to twelve experimental plots (13 m × 13 m each): crab removal, disturbance control and control. Within one year, the number of U. cordatus burrows inside the four removal plots decreased on average to 52% of the initial number. Despite this distinct reduction in burrow density of this large bioturbator, none of the measured parameters differed between treatments. Instead, most parameters were clearly influenced by seasonal changes in precipitation. Hence, in the studied R. mangle forest, abiotic factors seem to be more important drivers of ecosystem processes than factors mediated by U. cordatus, at least within the studied timespan of one year. PMID:27907093

Mangrove Crab Ucides cordatus Removal Does Not Affect Sediment Parameters and Stipule Production in a One Year Experiment in Northern Brazil.

PubMed

Pülmanns, Nathalie; Mehlig, Ulf; Nordhaus, Inga; Saint-Paul, Ulrich; Diele, Karen

2016-01-01

Mangrove crabs influence ecosystem processes through bioturbation and/or litter feeding. In Brazilian mangroves, the abundant and commercially important crab Ucides cordatus is the main faunal modifier of microtopography establishing up to 2 m deep burrows. They process more than 70% of the leaf litter and propagule production, thus promoting microbial degradation of detritus and benefiting microbe-feeding fiddler crabs. The accelerated nutrient turn-over and increased sediment oxygenation mediated by U. cordatus may enhance mangrove tree growth. Such positive feed-back loop was tested in North Brazil through a one year crab removal experiment simulating increased harvesting rates in a mature Rhizophora mangle forest. Investigated response parameters were sediment salinity, organic matter content, CO2 efflux rates of the surface sediment, and reduction potential. We also determined stipule fall of the mangrove tree R. mangle as a proxy for tree growth. Three treatments were applied to twelve experimental plots (13 m × 13 m each): crab removal, disturbance control and control. Within one year, the number of U. cordatus burrows inside the four removal plots decreased on average to 52% of the initial number. Despite this distinct reduction in burrow density of this large bioturbator, none of the measured parameters differed between treatments. Instead, most parameters were clearly influenced by seasonal changes in precipitation. Hence, in the studied R. mangle forest, abiotic factors seem to be more important drivers of ecosystem processes than factors mediated by U. cordatus, at least within the studied timespan of one year.

Impact of parameter fluctuations on the performance of ethanol precipitation in production of Re Du Ning Injections, based on HPLC fingerprints and principal component analysis.

PubMed

Sun, Li-Qiong; Wang, Shu-Yao; Li, Yan-Jing; Wang, Yong-Xiang; Wang, Zhen-Zhong; Huang, Wen-Zhe; Wang, Yue-Sheng; Bi, Yu-An; Ding, Gang; Xiao, Wei

2016-01-01

The present study was designed to determine the relationships between the performance of ethanol precipitation and seven process parameters in the ethanol precipitation process of Re Du Ning Injections, including concentrate density, concentrate temperature, ethanol content, flow rate and stir rate in the addition of ethanol, precipitation time, and precipitation temperature. Under the experimental and simulated production conditions, a series of precipitated resultants were prepared by changing these variables one by one, and then examined by HPLC fingerprint analyses. Different from the traditional evaluation model based on single or a few constituents, the fingerprint data of every parameter fluctuation test was processed with Principal Component Analysis (PCA) to comprehensively assess the performance of ethanol precipitation. Our results showed that concentrate density, ethanol content, and precipitation time were the most important parameters that influence the recovery of active compounds in precipitation resultants. The present study would provide some reference for pharmaceutical scientists engaged in research on pharmaceutical process optimization and help pharmaceutical enterprises adapt a scientific and reasonable cost-effective approach to ensure the batch-to-batch quality consistency of the final products. Copyright © 2016 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

A novel approach for calculating shelf life of minimally processed vegetables.

PubMed

Corbo, Maria Rosaria; Del Nobile, Matteo Alessandro; Sinigaglia, Milena

2006-01-15

Shelf life of minimally processed vegetables is often calculated by using the kinetic parameters of Gompertz equation as modified by Zwietering et al. [Zwietering, M.H., Jongenburger, F.M., Roumbouts, M., van't Riet, K., 1990. Modelling of the bacterial growth curve. Applied and Environmental Microbiology 56, 1875-1881.] taking 5x10(7) CFU/g as the maximum acceptable contamination value consistent with acceptable quality of these products. As this method does not allow estimation of the standard errors of the shelf life, in this paper the modified Gompertz equation was re-parameterized to directly include the shelf life as a fitting parameter among the Gompertz parameters. Being the shelf life a fitting parameter is possible to determine its confidence interval by fitting the proposed equation to the experimental data. The goodness-of-fit of this new equation was tested by using mesophilic bacteria cell loads from different minimally processed vegetables (packaged fresh-cut lettuce, fennel and shredded carrots) that differed for some process operations or for package atmosphere. The new equation was able to describe the data well and to estimate the shelf life. The results obtained emphasize the importance of using the standard errors for the shelf life value to show significant differences among the samples.

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

Lunar ash flow with heat transfer.

NASA Technical Reports Server (NTRS)

Pai, S. I.; Hsieh, T.; O'Keefe, J. A.

1972-01-01

The most important heat-transfer process in the ash flow under consideration is heat convection. Besides the four important nondimensional parameters of isothermal ash flow (Pai et al., 1972), we have three additional important nondimensional parameters: the ratio of the specific heat of the gas, the ratio of the specific heat of the solid particles to that of gas, and the Prandtl number. We reexamine the one dimensional steady ash flow discussed by Pai et al. (1972) by including the effects of heat transfer. Numerical results for the pressure, temperature, density of the gas, velocities of gas and solid particles, and volume fraction of solid particles as function of altitude for various values of the Jeffreys number, initial velocity ratio, and two different gas species (steam and hydrogen) are presented.

Modeling the compliance of polyurethane nanofiber tubes for artificial common bile duct

NASA Astrophysics Data System (ADS)

Moazeni, Najmeh; Vadood, Morteza; Semnani, Dariush; Hasani, Hossein

2018-02-01

The common bile duct is one of the body’s most sensitive organs and a polyurethane nanofiber tube can be used as a prosthetic of the common bile duct. The compliance is one of the most important properties of prosthetic which should be adequately compliant as long as possible to keep the behavioral integrity of prosthetic. In the present paper, the prosthetic compliance was measured and modeled using regression method and artificial neural network (ANN) based on the electrospinning process parameters such as polymer concentration, voltage, tip-to-collector distance and flow rate. Whereas, the ANN model contains different parameters affecting on the prediction accuracy directly, the genetic algorithm (GA) was used to optimize the ANN parameters. Finally, it was observed that the optimized ANN model by GA can predict the compliance with high accuracy (mean absolute percentage error = 8.57%). Moreover, the contribution of variables on the compliance was investigated through relative importance analysis and the optimum values of parameters for ideal compliance were determined.

Remote sensing of wetland parameters related to carbon cycling

NASA Technical Reports Server (NTRS)

Bartlett, David S.; Johnson, Robert W.

1985-01-01

Measurement of the rates of important biogeochemical fluxes on regional or global scales is vital to understanding the geochemical and climatic consequences of natural biospheric processes and of human intervention in those processes. Remote data gathering and interpretation techniques were used to examine important cycling processes taking place in wetlands over large geographic expanses. Large area estimation of vegetative biomass and productivity depends upon accurate, consistent measurements of canopy spectral reflectance and upon wide applicability of algorithms relating reflectance to biometric parameters. Results of the use of airborne multispectral scanner data to map above-ground biomass in a Delaware salt marsh are shown. The mapping uses an effective algorithm linking biomass to measured spectral reflectance and a means to correct the scanner data for large variations in the angle of observation of the canopy. The consistency of radiometric biomass algorithms for marsh grass when they are applied over large latitudinal and tidal range gradients were also examined. Results of a 1 year study of methane emissions from tidal wetlands along a salinity gradient show marked effects of temperature, season, and pore-water chemistry in mediating flux to the atmosphere.

Part height control of laser metal additive manufacturing process

NASA Astrophysics Data System (ADS)

Pan, Yu-Herng

Laser Metal Deposition (LMD) has been used to not only make but also repair damaged parts in a layer-by-layer fashion. Parts made in this manner may produce less waste than those made through conventional machining processes. However, a common issue of LMD involves controlling the deposition's layer thickness. Accuracy is important, and as it increases, both the time required to produce the part and the material wasted during the material removal process (e.g., milling, lathe) decrease. The deposition rate is affected by multiple parameters, such as the powder feed rate, laser input power, axis feed rate, material type, and part design, the values of each of which may change during the LMD process. Using a mathematical model to build a generic equation that predicts the deposition's layer thickness is difficult due to these complex parameters. In this thesis, we propose a simple method that utilizes a single device. This device uses a pyrometer to monitor the current build height, thereby allowing the layer thickness to be controlled during the LMD process. This method also helps the LMD system to build parts even with complex parameters and to increase material efficiency.

Effect of Laser Power and Gas Flow Rate on Properties of Directed Energy Deposition of Titanium Alloy

NASA Astrophysics Data System (ADS)

Mahamood, Rasheedat M.

2018-03-01

Laser metal deposition (LMD) process belongs to the directed energy deposition class of additive manufacturing processes. It is an important manufacturing technology with lots of potentials especially for the automobile and aerospace industries. The laser metal deposition process is fairly new, and the process is very sensitive to the processing parameters. There is a high level of interactions among these process parameters. The surface finish of part produced using the laser metal deposition process is dependent on the processing parameters. Also, the economy of the LMD process depends largely on steps taken to eliminate or reduce the need for secondary finishing operations. In this study, the influence of laser power and gas flow rate on the microstructure, microhardness and surface finish produced during the laser metal deposition of Ti6Al4V was investigated. The laser power was varied between 1.8 kW and 3.0 kW, while the gas flow rate was varied between 2 l/min and 4 l/min. The microstructure was studied under an optical microscope, the microhardness was studied using a Metkon microhardness indenter, while the surface roughness was studied using a Jenoptik stylus surface analyzer. The results showed that better surface finish was produced at a laser power of 3.0 kW and a gas flow rate of 4 l/min.

Abiotic and biotic dynamics during the initial stages of high solids switchgrass degradation.

PubMed

Fontenelle, L T; Corgie, S C; Walker, L P

2011-07-01

An understanding of the underlying dynamics of how biotic variables drive changes in abiotic parameters in the early stages of biomass biodegradation is essential for better control of the process. Probe hybridization was used to quantitatively study the growth of bacteria, yeast and fungi for three levels of initial moisture content (60, 65 and 75% MC) over a period of 64 h. Changes in abiotic parameters were also documented. By 64 h, samples were significantly differentiated both in temporal and spatial dimension, proving that considerable changes had occurred in these initial stages. Maximum carbon (C) conversion occurred in the 75% MC reactor at a peak value of 49%, with 40% and 37% in the 65 and 60% MC reactors, respectively. Higher temperature, higher pH, higher rates of O2 consumption and CO2 evolution were also observed in the highest moisture reactor; suggesting that of the three MCs studied, 75% MC was the optimal one for the process. MC during the process also proved to be important because it greatly influenced variation in the spatial dimension, further underscoring the importance of characterizing changes with bed height. Most importantly, we were able to positively correlate the rate of substrate degradation with bacterial biomass levels and highlight the critical role of bacteria in biological decomposition.

MicroCT parameters for multimaterial elements assessment

NASA Astrophysics Data System (ADS)

de Araújo, Olga M. O.; Silva Bastos, Jaqueline; Machado, Alessandra S.; dos Santos, Thaís M. P.; Ferreira, Cintia G.; Rosifini Alves Claro, Ana Paula; Lopes, Ricardo T.

2018-03-01

Microtomography is a non-destructive testing technique for quantitative and qualitative analysis. The investigation of multimaterial elements with great difference of density can result in artifacts that degrade image quality depending on combination of additional filter. The aim of this study is the selection of parameters most appropriate for analysis of bone tissue with metallic implant. The results show the simulation with MCNPX code for the distribution of energy without additional filter, with use of aluminum, copper and brass filters and their respective reconstructed images showing the importance of the choice of these parameters in image acquisition process on computed microtomography.

Understanding identifiability as a crucial step in uncertainty assessment

NASA Astrophysics Data System (ADS)

Jakeman, A. J.; Guillaume, J. H. A.; Hill, M. C.; Seo, L.

2016-12-01

The topic of identifiability analysis offers concepts and approaches to identify why unique model parameter values cannot be identified, and can suggest possible responses that either increase uniqueness or help to understand the effect of non-uniqueness on predictions. Identifiability analysis typically involves evaluation of the model equations and the parameter estimation process. Non-identifiability can have a number of undesirable effects. In terms of model parameters these effects include: parameters not being estimated uniquely even with ideal data; wildly different values being returned for different initialisations of a parameter optimisation algorithm; and parameters not being physically meaningful in a model attempting to represent a process. This presentation illustrates some of the drastic consequences of ignoring model identifiability analysis. It argues for a more cogent framework and use of identifiability analysis as a way of understanding model limitations and systematically learning about sources of uncertainty and their importance. The presentation specifically distinguishes between five sources of parameter non-uniqueness (and hence uncertainty) within the modelling process, pragmatically capturing key distinctions within existing identifiability literature. It enumerates many of the various approaches discussed in the literature. Admittedly, improving identifiability is often non-trivial. It requires thorough understanding of the cause of non-identifiability, and the time, knowledge and resources to collect or select new data, modify model structures or objective functions, or improve conditioning. But ignoring these problems is not a viable solution. Even simple approaches such as fixing parameter values or naively using a different model structure may have significant impacts on results which are too often overlooked because identifiability analysis is neglected.

Manufacturing of hybrid aluminum copper joints by electromagnetic pulse welding - Identification of quantitative process windows

NASA Astrophysics Data System (ADS)

Psyk, Verena; Scheffler, Christian; Linnemann, Maik; Landgrebe, Dirk

2017-10-01

Compared to conventional joining techniques, electromagnetic pulse welding offers important advantages especially when it comes to dissimilar material connections as e.g. copper aluminum welds. However, due to missing guidelines and tools for process design, the process has not been widely implemented in industrial production, yet. In order to contribute to overcoming this obstacle, a combined numerical and experimental process analysis for electromagnetic pulse welding of Cu-DHP and EN AW-1050 was carried out and the results were consolidated in a quantitative collision parameter based process window.

Finite Element Method (FEM) Modeling of Freeze-drying: Monitoring Pharmaceutical Product Robustness During Lyophilization.

PubMed

Chen, Xiaodong; Sadineni, Vikram; Maity, Mita; Quan, Yong; Enterline, Matthew; Mantri, Rao V

2015-12-01

Lyophilization is an approach commonly undertaken to formulate drugs that are unstable to be commercialized as ready to use (RTU) solutions. One of the important aspects of commercializing a lyophilized product is to transfer the process parameters that are developed in lab scale lyophilizer to commercial scale without a loss in product quality. This process is often accomplished by costly engineering runs or through an iterative process at the commercial scale. Here, we are highlighting a combination of computational and experimental approach to predict commercial process parameters for the primary drying phase of lyophilization. Heat and mass transfer coefficients are determined experimentally either by manometric temperature measurement (MTM) or sublimation tests and used as inputs for the finite element model (FEM)-based software called PASSAGE, which computes various primary drying parameters such as primary drying time and product temperature. The heat and mass transfer coefficients will vary at different lyophilization scales; hence, we present an approach to use appropriate factors while scaling-up from lab scale to commercial scale. As a result, one can predict commercial scale primary drying time based on these parameters. Additionally, the model-based approach presented in this study provides a process to monitor pharmaceutical product robustness and accidental process deviations during Lyophilization to support commercial supply chain continuity. The approach presented here provides a robust lyophilization scale-up strategy; and because of the simple and minimalistic approach, it will also be less capital intensive path with minimal use of expensive drug substance/active material.

Disease management programs for type 2 diabetes in Germany: a systematic literature review evaluating effectiveness.

PubMed

Fuchs, Sabine; Henschke, Cornelia; Blümel, Miriam; Busse, Reinhard

2014-06-27

Disease management programs (DMPs) are intended to improve the care of persons with chronic diseases. Despite numerous studies there is no unequivocal evidence about the effectiveness of DMPs in Germany. We conducted a systematic literature review in the MEDLINE, EMBASE, Cochrane Library, and CCMed databases. Our analysis included all controlled studies in which patients with type 2 diabetes enrolled in a DMP were compared to type 2 diabetes patients receiving routine care with respect to process, outcome, and economic parameters. The 9 studies included in the analysis were highly divergent with respect to their characteristics and the process and outcome parameters studied in each. No study had data beyond the year 2008. In 3 publications, the DMP patients had a lower mortality than the control patients (2.3%, 11.3%, and 7.17% versus 4.7%, 14.4%, and 14.72%). In 2 publications, DMP participation was found to be associated with a mean survival time of 1044.94 (± 189.87) days, as against 985.02 (± 264.68) in the control group. No consistent effect was seen with respect to morbidity, quality of life, or economic parameters. 7 publications from 5 studies revealed positive effects on process parameters for DMP participants. The observed beneficial trends with respect to mortality and survival time, as well as improvements in process parameters, indicate that DMPs can, in fact, improve the care of patients with diabetes. Further evaluation is needed, because some changes in outcome parameters (an important indicator of the quality of care) may only be observable over a longer period of time.

Supercritical-Multiple-Solvent Extraction From Coal

NASA Technical Reports Server (NTRS)

Corcoran, W.; Fong, W.; Pichaichanarong, P.; Chan, P.; Lawson, D.

1983-01-01

Large and small molecules dissolve different constituents. Experimental apparatus used to test supercritical extraction of hydrogen rich compounds from coal in various organic solvents. In decreasing order of importance, relevant process parameters were found to be temperature, solvent type, pressure, and residence time.

Global sensitivity analysis of a local water balance model predicting evaporation, water yield and drought

NASA Astrophysics Data System (ADS)

Speich, Matthias; Zappa, Massimiliano; Lischke, Heike

2017-04-01

Evaporation and transpiration affect both catchment water yield and the growing conditions for vegetation. They are driven by climate, but also depend on vegetation, soil and land surface properties. In hydrological and land surface models, these properties may be included as constant parameters, or as state variables. Often, little is known about the effect of these variables on model outputs. In the present study, the effect of surface properties on evaporation was assessed in a global sensitivity analysis. To this effect, we developed a simple local water balance model combining state-of-the-art process formulations for evaporation, transpiration and soil water balance. The model is vertically one-dimensional, and the relative simplicity of its process formulations makes it suitable for integration in a spatially distributed model at regional scale. The main model outputs are annual total evaporation (TE, i.e. the sum of transpiration, soil evaporation and interception), and a drought index (DI), which is based on the ratio of actual and potential transpiration. This index represents the growing conditions for forest trees. The sensitivity analysis was conducted in two steps. First, a screening analysis was applied to identify unimportant parameters out of an initial set of 19 parameters. In a second step, a statistical meta-model was applied to a sample of 800 model runs, in which the values of the important parameters were varied. Parameter effect and interactions were analyzed with effects plots. The model was driven with forcing data from ten meteorological stations in Switzerland, representing a wide range of precipitation regimes across a strong temperature gradient. Of the 19 original parameters, eight were identified as important in the screening analysis. Both steps highlighted the importance of Plant Available Water Capacity (AWC) and Leaf Area Index (LAI). However, their effect varies greatly across stations. For example, while a transition from a sparse to a closed forest canopy has almost no effect on annual TE at warm and dry sites, it increases TE by up to 100 mm/year at cold-humid and warm-humid sites. Further parameters of importance describe infiltration, as well as canopy resistance and its response to environmental variables. This study offers insights for future development of hydrological and ecohydrological models. First, it shows that although local water balance is primarily controlled by climate, the vegetation and soil parameters may have a large impact on the outputs. Second, it indicates that modeling studies should prioritize a realistic parameterization of LAI and AWC, while other parameters may be set to fixed values. Third, it illustrates to which extent parameter effect and interactions depend on local climate.

Environmental, Human Health and Socio-Economic Effects of Cement Powders: The Multicriteria Analysis as Decisional Methodology.

PubMed

Moretti, Laura; Di Mascio, Paola; Bellagamba, Simona

2017-06-16

The attention to sustainability-related issues has grown fast in recent decades. The experience gained with these themes reveals the importance of considering this topic in the construction industry, which represents an important sector throughout the world. This work consists on conducting a multicriteria analysis of four cement powders, with the objective of calculating and analysing the environmental, human health and socio-economic effects of their production processes. The economic, technical, environmental and safety performances of the examined powders result from official, both internal and public, documents prepared by the producers. The Analytic Hierarchy Process permitted to consider several indicators (i.e., environmental, human health related and socio-economic parameters) and to conduct comprehensive and unbiased analyses which gave the best, most sustainable cement powder. As assumed in this study, the contribution of each considered parameter to the overall sustainability has a different incidence, therefore the procedure could be used to support on-going sustainability efforts under different conditions. The results also prove that it is not appropriate to regard only one parameter to identify the 'best' cement powder, but several impact categories should be considered and analysed if there is an interest for pursuing different, often conflicting interests.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion.

PubMed

Goldrick, Stephen; Holmes, William; Bond, Nicholas J; Lewis, Gareth; Kuiper, Marcel; Turner, Richard; Farid, Suzanne S

2017-10-01

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (Ambr TM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on-line and off-line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale-up. Biotechnol. Bioeng. 2017;114: 2222-2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Regional probability distribution of the annual reference evapotranspiration and its effective parameters in Iran

NASA Astrophysics Data System (ADS)

Khanmohammadi, Neda; Rezaie, Hossein; Montaseri, Majid; Behmanesh, Javad

2017-10-01

The reference evapotranspiration (ET0) plays an important role in water management plans in arid or semi-arid countries such as Iran. For this reason, the regional analysis of this parameter is important. But, ET0 process is affected by several meteorological parameters such as wind speed, solar radiation, temperature and relative humidity. Therefore, the effect of distribution type of effective meteorological variables on ET0 distribution was analyzed. For this purpose, the regional probability distribution of the annual ET0 and its effective parameters were selected. Used data in this research was recorded data at 30 synoptic stations of Iran during 1960-2014. Using the probability plot correlation coefficient (PPCC) test and the L-moment method, five common distributions were compared and the best distribution was selected. The results of PPCC test and L-moment diagram indicated that the Pearson type III distribution was the best probability distribution for fitting annual ET0 and its four effective parameters. The results of RMSE showed that the ability of the PPCC test and L-moment method for regional analysis of reference evapotranspiration and its effective parameters was similar. The results also showed that the distribution type of the parameters which affected ET0 values can affect the distribution of reference evapotranspiration.

A Three-Parameter Model for Predicting Fatigue Life of Ductile Metals Under Constant Amplitude Multiaxial Loading

NASA Astrophysics Data System (ADS)

Liu, Jia; Li, Jing; Zhang, Zhong-ping

2013-04-01

In this article, a fatigue damage parameter is proposed to assess the multiaxial fatigue lives of ductile metals based on the critical plane concept: Fatigue crack initiation is controlled by the maximum shear strain, and the other important effect in the fatigue damage process is the normal strain and stress. This fatigue damage parameter introduces a stress-correlated factor, which describes the degree of the non-proportional cyclic hardening. Besides, a three-parameter multiaxial fatigue criterion is used to correlate the fatigue lifetime of metallic materials with the proposed damage parameter. Under the uniaxial loading, this three-parameter model reduces to the recently developed Zhang's model for predicting the uniaxial fatigue crack initiation life. The accuracy and reliability of this three-parameter model are checked against the experimental data found in literature through testing six different ductile metals under various strain paths with zero/non-zero mean stress.

Observing continuous change in heart rate variability and photoplethysmography-derived parameters during the process of pain production/relief with thermal stimuli.

PubMed

Ye, Jing-Jhao; Lee, Kuan-Ting; Lin, Jing-Siang; Chuang, Chiung-Cheng

2017-01-01

Continuously monitoring and efficiently managing pain has become an important issue. However, no study has investigated a change in physiological parameters during the process of pain production/relief. This study modeled the process of pain production/relief using ramped thermal stimulation (no pain: 37°C water, process of pain production: a heating rate of 1°C/min, and subject feels pain: water kept at the painful temperature for each subject, with each segment lasting 10 min). In this duration, the variation of the heat rate variability and photoplethysmography-derived parameters was observed. A total of 40 healthy individuals participated: 30 in the trial group (14 males and 16 females with a mean age of 22.5±1.9 years) and 10 in the control group (7 males and 3 females with a mean age of 22.5±1.3 years). The results showed that the numeric rating scale value was 5.03±1.99 when the subjects felt pain, with a temperature of 43.54±1.70°C. Heart rate, R-R interval, low frequency, high frequency, photoplethysmography amplitude, baseline, and autonomic nervous system state showed significant changes during the pain production process, but these changes differed during the period Segment D (painful temperature 10: min). In summary, the study observed that physiological parameters changed qualitatively during the process of pain production and relief and found that the high frequency, low frequency, and photoplethysmography parameters seemed to have different responses in four situations (no pain, pain production, pain experienced, and pain relief). The trends of these variations may be used as references in the clinical setting for continuously observing pain intensity.

Estimation of parameters in Shot-Noise-Driven Doubly Stochastic Poisson processes using the EM algorithm--modeling of pre- and postsynaptic spike trains.

PubMed

Mino, H

2007-01-01

To estimate the parameters, the impulse response (IR) functions of some linear time-invariant systems generating intensity processes, in Shot-Noise-Driven Doubly Stochastic Poisson Process (SND-DSPP) in which multivariate presynaptic spike trains and postsynaptic spike trains can be assumed to be modeled by the SND-DSPPs. An explicit formula for estimating the IR functions from observations of multivariate input processes of the linear systems and the corresponding counting process (output process) is derived utilizing the expectation maximization (EM) algorithm. The validity of the estimation formula was verified through Monte Carlo simulations in which two presynaptic spike trains and one postsynaptic spike train were assumed to be observable. The IR functions estimated on the basis of the proposed identification method were close to the true IR functions. The proposed method will play an important role in identifying the input-output relationship of pre- and postsynaptic neural spike trains in practical situations.

Modeling and flow analysis of pure nylon polymer for injection molding process

NASA Astrophysics Data System (ADS)

Nuruzzaman, D. M.; Kusaseh, N.; Basri, S.; Oumer, A. N.; Hamedon, Z.

2016-02-01

In the production of complex plastic parts, injection molding is one of the most popular industrial processes. This paper addresses the modeling and analysis of the flow process of the nylon (polyamide) polymer for injection molding process. To determine the best molding conditions, a series of simulations are carried out using Autodesk Moldflow Insight software and the processing parameters are adjusted. This mold filling commercial software simulates the cavity filling pattern along with temperature and pressure distributions in the mold cavity. In the modeling, during the plastics flow inside the mold cavity, different flow parameters such as fill time, pressure, temperature, shear rate and warp at different locations in the cavity are analyzed. Overall, this Moldflow is able to perform a relatively sophisticated analysis of the flow process of pure nylon. Thus the prediction of the filling of a mold cavity is very important and it becomes useful before a nylon plastic part to be manufactured.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface-Subsurface Process (CSSP) land surface model

NASA Astrophysics Data System (ADS)

Gan, Yanjun; Liang, Xin-Zhong; Duan, Qingyun; Choi, Hyun Il; Dai, Yongjiu; Wu, Huan

2015-06-01

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol' sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol' sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture. This article was corrected on 26 JUN 2015. See the end of the full text for details.

Applicability of Different Hydraulic Parameters to Describe Soil Detachment in Eroding Rills

PubMed Central

Wirtz, Stefan; Seeger, Manuel; Zell, Andreas; Wagner, Christian; Wagner, Jean-Frank; Ries, Johannes B.

2013-01-01

This study presents the comparison of experimental results with assumptions used in numerical models. The aim of the field experiments is to test the linear relationship between different hydraulic parameters and soil detachment. For example correlations between shear stress, unit length shear force, stream power, unit stream power and effective stream power and the detachment rate does not reveal a single parameter which consistently displays the best correlation. More importantly, the best fit does not only vary from one experiment to another, but even between distinct measurement points. Different processes in rill erosion are responsible for the changing correlations. However, not all these procedures are considered in soil erosion models. Hence, hydraulic parameters alone are not sufficient to predict detachment rates. They predict the fluvial incising in the rill's bottom, but the main sediment sources are not considered sufficiently in its equations. The results of this study show that there is still a lack of understanding of the physical processes underlying soil erosion. Exerted forces, soil stability and its expression, the abstraction of the detachment and transport processes in shallow flowing water remain still subject of unclear description and dependence. PMID:23717669

Numerical simulation of hydrogen fluorine overtone chemical lasers

NASA Astrophysics Data System (ADS)

Chen, Jinbao; Jiang, Zhongfu; Hua, Weihong; Liu, Zejin; Shu, Baihong

1998-08-01

A two-dimensional program was applied to simulate the chemical dynamic process, gas dynamic process and lasing process of a combustion-driven CW HF overtone chemical lasers. Some important parameters in the cavity were obtained. The calculated results included HF molecule concentration on each vibration energy level while lasing, averaged pressure and temperature, zero power gain coefficient of each spectral line, laser spectrum, the averaged laser intensity, output power, chemical efficiency and the length of lasing zone.

Case Studies in Modelling, Control in Food Processes.

PubMed

Glassey, J; Barone, A; Montague, G A; Sabou, V

This chapter discusses the importance of modelling and control in increasing food process efficiency and ensuring product quality. Various approaches to both modelling and control in food processing are set in the context of the specific challenges in this industrial sector and latest developments in each area are discussed. Three industrial case studies are used to demonstrate the benefits of advanced measurement, modelling and control in food processes. The first case study illustrates the use of knowledge elicitation from expert operators in the process for the manufacture of potato chips (French fries) and the consequent improvements in process control to increase the consistency of the resulting product. The second case study highlights the economic benefits of tighter control of an important process parameter, moisture content, in potato crisp (chips) manufacture. The final case study describes the use of NIR spectroscopy in ensuring effective mixing of dry multicomponent mixtures and pastes. Practical implementation tips and infrastructure requirements are also discussed.

Effect of Process Parameters on Catalytic Incineration of Solvent Emissions

PubMed Central

Ojala, Satu; Lassi, Ulla; Perämäki, Paavo; Keiski, Riitta L.

2008-01-01

Catalytic oxidation is a feasible and affordable technology for solvent emission abatement. However, finding optimal operation conditions is important, since they are strongly dependent on the application area of VOC incineration. This paper presents the results of the laboratory experiments concerning four most central parameters, that is, effects of concentration, gas hourly space velocity (GHSV), temperature, and moisture on the oxidation of n-butyl acetate. Both fresh and industrially aged commercial Pt/Al2O3 catalysts were tested to determine optimal process conditions and the significance order and level of selected parameters. The effects of these parameters were evaluated by computer-aided statistical experimental design. According to the results, GHSV was the most dominant parameter in the oxidation of n-butyl acetate. Decreasing GHSV and increasing temperature increased the conversion of n-butyl acetate. The interaction effect of GHSV and temperature was more significant than the effect of concentration. Both of these affected the reaction by increasing the conversion of n-butyl acetate. Moisture had only a minor decreasing effect on the conversion, but it also decreased slightly the formation of by products. Ageing did not change the significance order of the above-mentioned parameters, however, the effects of individual parameters increased slightly as a function of ageing. PMID:18584032

Simulation of the Press Hardening Process and Prediction of the Final Mechanical Material Properties

NASA Astrophysics Data System (ADS)

Hochholdinger, Bernd; Hora, Pavel; Grass, Hannes; Lipp, Arnulf

2011-08-01

Press hardening is a well-established production process in the automotive industry today. The actual trend of this process technology points towards the manufacturing of parts with tailored properties. Since the knowledge of the mechanical properties of a structural part after forming and quenching is essential for the evaluation of for example the crash performance, an accurate as possible virtual assessment of the production process is more than ever necessary. In order to achieve this, the definition of reliable input parameters and boundary conditions for the thermo-mechanically coupled simulation of the process steps is required. One of the most important input parameters, especially regarding the final properties of the quenched material, is the contact heat transfer coefficient (IHTC). The CHTC depends on the effective pressure or the gap distance between part and tool. The CHTC at different contact pressures and gap distances is determined through inverse parameter identification. Furthermore a simulation strategy for the subsequent steps of the press hardening process as well as adequate modeling approaches for part and tools are discussed. For the prediction of the yield curves of the material after press hardening a phenomenological model is presented. This model requires the knowledge of the microstructure within the part. By post processing the nodal temperature history with a CCT diagram the quantitative distribution of the phase fractions martensite, bainite, ferrite and pearlite after press hardening is determined. The model itself is based on a Hockett-Sherby approach with the Hockett-Sherby parameters being defined in function of the phase fractions and a characteristic cooling rate.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

DOE PAGES

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; ...

2017-02-23

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

Ga- and N-polar GaN Growths on SiC Substrate

DTIC Science & Technology

2018-03-15

a transition process of a two-section NR are formulated and numerically studied to show the consistent results with experimental data. The relative...contributions of the VLS and VS growths in such a transition process are also numerically illustrated. Besides, the experimentally observed decrease... experimental data, a few important kinetic parameters can be determined. The anti-reflection functions of a surface nanostructure, including

Density of Spray-Formed Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kevin M. McHugh; Volker Uhlenwinkel; Nils Ellendr

2008-06-01

Spray Forming is an advanced materials processing technology that transforms molten metal into a near-net-shape solid by depositing atomized droplets onto a substrate. Depending on the application, the spray-formed material may be used in the as-deposited condition or it may undergo post-deposition processing. Regardless, the density of the as-deposited material is an important issue. Porosity is detrimental because it can significantly reduce strength, toughness, hardness and other properties. While it is not feasible to achieve fully-dense material in the as-deposited state, density greater than 99% of theoretical density is possible if the atomization and impact conditions are optimized. Thermal conditionsmore » at the deposit surface and droplet impact angle are key processing parameters that influence the density of the material. This paper examines the factors that contribute to porosity formation during spray forming and illustrates that very high as-deposited density is achieved by optimizing processing parameters.« less

On storm movement and its applications

NASA Astrophysics Data System (ADS)

Niemczynowicz, Janusz

Rainfall-runoff models applicable for design and analysis of sewage systems in urban areas are further developed in order to represent better different physical processes going on on an urban catchment. However, one important part of the modelling procedure, the generation of the rainfall input is still a weak point. The main problem is lack of adequate rainfall data which represent temporal and spatial variations of the natural rainfall process. Storm movement is a natural phenomenon which influences urban runoff. However, the rainfall movement and its influence on runoff generation process is not represented in presently available urban runoff simulation models. Physical description of the rainfall movement and its parameters is given based on detailed measurements performed on twelve gauges in Lund, Sweden. The paper discusses the significance of the rainfall movement on the runoff generation process and gives suggestions how the rainfall movement parameters may be used in runoff modelling.

A Theory of Exoplanet Transits with Light Scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Tyler D., E-mail: tydrobin@ucsc.edu

Exoplanet transit spectroscopy enables the characterization of distant worlds, and will yield key results for NASA's James Webb Space Telescope . However, transit spectra models are often simplified, omitting potentially important processes like refraction and multiple scattering. While the former process has seen recent development, the effects of light multiple scattering on exoplanet transit spectra have received little attention. Here, we develop a detailed theory of exoplanet transit spectroscopy that extends to the full refracting and multiple scattering case. We explore the importance of scattering for planet-wide cloud layers, where the relevant parameters are the slant scattering optical depth, themore » scattering asymmetry parameter, and the angular size of the host star. The latter determines the size of the “target” for a photon that is back-mapped from an observer. We provide results that straightforwardly indicate the potential importance of multiple scattering for transit spectra. When the orbital distance is smaller than 10–20 times the stellar radius, multiple scattering effects for aerosols with asymmetry parameters larger than 0.8–0.9 can become significant. We provide examples of the impacts of cloud/haze multiple scattering on transit spectra of a hot Jupiter-like exoplanet. For cases with a forward and conservatively scattering cloud/haze, differences due to multiple scattering effects can exceed 200 ppm, but shrink to zero at wavelength ranges corresponding to strong gas absorption or when the slant optical depth of the cloud exceeds several tens. We conclude with a discussion of types of aerosols for which multiple scattering in transit spectra may be important.« less

Design of distributed systems of hydrolithosphere processes management. A synthesis of distributed management systems

NASA Astrophysics Data System (ADS)

Pershin, I. M.; Pervukhin, D. A.; Ilyushin, Y. V.; Afanaseva, O. V.

2017-10-01

The paper considers an important problem of designing distributed systems of hydrolithosphere processes management. The control actions on the hydrolithosphere processes under consideration are implemented by a set of extractive wells. The article shows the method of defining the approximation links for description of the dynamic characteristics of hydrolithosphere processes. The structure of distributed regulators, used in the management systems by the considered processes, is presented. The paper analyses the results of the synthesis of the distributed management system and the results of modelling the closed-loop control system by the parameters of the hydrolithosphere process.

Ultrasonic cleaning: Fundamental theory and application

NASA Technical Reports Server (NTRS)

Fuchs, F. John

1995-01-01

This presentation describes: the theory of ultrasonics, cavitation and implosion; the importance and application of ultrasonics in precision cleaning; explanations of ultrasonic cleaning equipment options and their application; process parameters for ultrasonic cleaning; and proper operation of ultrasonic cleaning equipment to achieve maximum results.

A REVIEW OF STRUCTURE-BASED BIODEGRADATION ESTIMATION METHODS. (R825370C077)

EPA Science Inventory

Biodegradation, being the principal abatement process in the environment, is the most important parameter influencing the toxicity, persistence, and ultimate fate in aquatic and terrestrial ecosystems. Biodegradation of an organic chemical in natural systems may be classified ...

A REVIEW OF STRUCTURE-BASED BIODEGRADATION ESTIMATION METHODS. (R825370C064)

EPA Science Inventory

Biodegradation, being the principal abatement process in the environment, is the most important parameter influencing the toxicity, persistence, and ultimate fate in aquatic and terrestrial ecosystems. Biodegradation of an organic chemical in natural systems may be classified ...

Developing an economical and reliable test for measuring the resilient modulus and Poisson's ratio of subgrade.

DOT National Transportation Integrated Search

2010-11-01

The resilient modulus and Poissons ratio of base and sublayers in highway use are : important parameters in design and quality control process. The currently used techniques : include CBR (California Bearing Ratio) test, resilient modulus test,...

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Physico-chemical, colorimetric, rheological parameters and chemometric discrimination of the origin of Mugil cephalus' roes during the manufacturing process of Bottarga.

PubMed

Caredda, Marco; Addis, Margherita; Pes, Massimo; Fois, Nicola; Sanna, Gabriele; Piredda, Giovanni; Sanna, Gavino

2018-06-01

The aim of this work was to measure the physico-chemical and the colorimetric parameters of ovaries from Mugil cephalus caught in the Tortolì lagoon (South-East coast of Sardinia) along the steps of the manufacturing process of Bottarga, together with the rheological parameters of the final product. A lowering of all CIELab coordinates (lightness, redness and yellowness) was observed during the manufacture process. All CIELab parameters were used to build a Linear Discriminant Analysis (LDA) predictive model able to determine in real time if the roes had been subdued to a freezing process, with a success in prediction of 100%. This model could be used to identify the origin of the roes, since only the imported ones are frozen. The major changes of all the studied parameters (p < 0.05) were noted in the drying step rather than in the salting step. After processing, Bottarga was characterized by a pH value of 5.46 (CV = 2.8) and a moisture content of 25% (CV = 8), whereas the typical per cent amounts of proteins, fat and NaCl, calculated as a percentage on the dried weight, were 56 (CV = 2), 34 (CV = 3) and 3.6 (CV = 17), respectively. The physical chemical changes of the roes during the manufacturing process were consistent for moisture, which decreased by 28%, whereas the protein and the fat contents on the dried weight got respectively lower of 3% and 2%. NaCl content increased by 3.1%. Principal Component Analyses (PCA) were also performed on all data to establish trends and relationships among all parameters. Hardness and consistency of Bottarga were negatively correlated with the moisture content (r = -0.87 and r = -0.88, respectively), while its adhesiveness was negatively correlated with the fat content (r = -0.68). Copyright © 2018. Published by Elsevier Ltd.

Study of spin-scan imaging for outer planets missions. [imaging techniques for Jupiter orbiter missions

NASA Technical Reports Server (NTRS)

Russell, E. E.; Chandos, R. A.; Kodak, J. C.; Pellicori, S. F.; Tomasko, M. G.

1974-01-01

The constraints that are imposed on the Outer Planet Missions (OPM) imager design are of critical importance. Imager system modeling analyses define important parameters and systematic means for trade-offs applied to specific Jupiter orbiter missions. Possible image sequence plans for Jupiter missions are discussed in detail. Considered is a series of orbits that allow repeated near encounters with three of the Jovian satellites. The data handling involved in the image processing is discussed, and it is shown that only minimal processing is required for the majority of images for a Jupiter orbiter mission.

Laboratory Studies of Homogeneous and Heterogeneous Chemical Processes of Importance in the Upper Atmosphere

NASA Technical Reports Server (NTRS)

Molina, Mario J.

2003-01-01

The objective of this study was to conduct measurements of chemical kinetics parameters for reactions of importance in the stratosphere and upper troposphere, and to study the interaction of trace gases with ice surfaces in order to elucidate the mechanism of heterogeneous chlorine activation processes, using both a theoretical and an experimental approach. The measurements were carried out under temperature and pressure conditions covering those applicable to the stratosphere and upper troposphere. The main experimental technique employed was turbulent flow-chemical ionization mass spectrometry, which is particularly well suited for investigations of radical-radical reactions.

Visualizing the deep end of sound: plotting multi-parameter results from infrasound data analysis

NASA Astrophysics Data System (ADS)

Perttu, A. B.; Taisne, B.

2016-12-01

Infrasound is sound below the threshold of human hearing: approximately 20 Hz. The field of infrasound research, like other waveform based fields relies on several standard processing methods and data visualizations, including waveform plots and spectrograms. The installation of the International Monitoring System (IMS) global network of infrasound arrays, contributed to the resurgence of infrasound research. Array processing is an important method used in infrasound research, however, this method produces data sets with a large number of parameters, and requires innovative plotting techniques. The goal in designing new figures is to be able to present easily comprehendible, and information-rich plots by careful selection of data density and plotting methods.

Evidences for dry deintercalation in layered compounds upon controlled surface charging in x-ray photoelectron spectroscopy

NASA Astrophysics Data System (ADS)

Feldman, Y.; Zak, A.; Tenne, R.; Cohen, H.

2003-09-01

Pronounced surface diffusion is observed during x-ray photoelectron spectroscopy measurements of 2H platelets and inorganic fullerene-like (IF) MS2 (M=W,Mo) powders, intercalated with alkaline (A=K,Na) elements. Using controlled surface charging the intercalants migrate towards the surface, where they oxidize. This dry deintercalation is controllable via external charging parameters, yet showing that internal chemical and structural parameters play an important role in the process. Diffusion rates out of 2H matrixes are generally higher than in corresponding IF samples. Clear differences are also found between Mo and W-based systems. Application of this approach into surface modification and processing is proposed.

Mice take calculated risks.

PubMed

Kheifets, Aaron; Gallistel, C R

2012-05-29

Animals successfully navigate the world despite having only incomplete information about behaviorally important contingencies. It is an open question to what degree this behavior is driven by estimates of stochastic parameters (brain-constructed models of the experienced world) and to what degree it is directed by reinforcement-driven processes that optimize behavior in the limit without estimating stochastic parameters (model-free adaptation processes, such as associative learning). We find that mice adjust their behavior in response to a change in probability more quickly and abruptly than can be explained by differential reinforcement. Our results imply that mice represent probabilities and perform calculations over them to optimize their behavior, even when the optimization produces negligible material gain.

Mice take calculated risks

PubMed Central

Kheifets, Aaron; Gallistel, C. R.

2012-01-01

Animals successfully navigate the world despite having only incomplete information about behaviorally important contingencies. It is an open question to what degree this behavior is driven by estimates of stochastic parameters (brain-constructed models of the experienced world) and to what degree it is directed by reinforcement-driven processes that optimize behavior in the limit without estimating stochastic parameters (model-free adaptation processes, such as associative learning). We find that mice adjust their behavior in response to a change in probability more quickly and abruptly than can be explained by differential reinforcement. Our results imply that mice represent probabilities and perform calculations over them to optimize their behavior, even when the optimization produces negligible material gain. PMID:22592792

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Washington University in St Louis, St Louis, MO; Li, H. Harlod

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The mostmore » important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.« less

Data integration for inference about spatial processes: A model-based approach to test and account for data inconsistency

PubMed Central

Pedrini, Paolo; Bragalanti, Natalia; Groff, Claudio

2017-01-01

Recently-developed methods that integrate multiple data sources arising from the same ecological processes have typically utilized structured data from well-defined sampling protocols (e.g., capture-recapture and telemetry). Despite this new methodological focus, the value of opportunistic data for improving inference about spatial ecological processes is unclear and, perhaps more importantly, no procedures are available to formally test whether parameter estimates are consistent across data sources and whether they are suitable for integration. Using data collected on the reintroduced brown bear population in the Italian Alps, a population of conservation importance, we combined data from three sources: traditional spatial capture-recapture data, telemetry data, and opportunistic data. We developed a fully integrated spatial capture-recapture (SCR) model that included a model-based test for data consistency to first compare model estimates using different combinations of data, and then, by acknowledging data-type differences, evaluate parameter consistency. We demonstrate that opportunistic data lend itself naturally to integration within the SCR framework and highlight the value of opportunistic data for improving inference about space use and population size. This is particularly relevant in studies of rare or elusive species, where the number of spatial encounters is usually small and where additional observations are of high value. In addition, our results highlight the importance of testing and accounting for inconsistencies in spatial information from structured and unstructured data so as to avoid the risk of spurious or averaged estimates of space use and consequently, of population size. Our work supports the use of a single modeling framework to combine spatially-referenced data while also accounting for parameter consistency. PMID:28973034

Relationship between selected physicochemical properties of peaty-mucks soils and main absorbance bands of its FTIR spectra*

NASA Astrophysics Data System (ADS)

Boguta, Patrycja; Sokolowska, Zofia

2013-04-01

Peatlands are a large reservoir of organic matter that is responsible for sorption properties, structure of soils and microbial activity. However, most of the peatlands in Poland have been drained and subjected to agricultural use. Processes of such kind cause acceleration of peat mass transformation to mucks. Changes in peat evolution under melioration processes are mostly characterised by mineralisation and humification. The above processes lead to changes in the morphological, chemical, biological and physical properties of peat soils. Knowledge about changes of these parameters is very important in suitable application of conditions and fertilisers in order to improve agricultural value of soil. One of the indicators which could describe the changes in peat mass could be the water holding capacity index proposed by Gawlik. This parameter characterises the secondary transformation processes taking place in soils. Mucking processes are also well described by humification indexes and organic/inorganic carbon content. However, changes of above physical and physicochemical properties of soils are also connected with changes of chemical structure of organic matter contained in soil material. Organic matter is a significant component of organic soils and it influences such important parameters of all soil like sorptivity. So that, it is also valuable to control state of functional groups which determine sorption capacity of soil. One of the methods which could be applied in this case is observation of absorbance values of functional groups in infrared spectra of samples. This is quick and method but it could be used only in approximate way because of some content of ash and inorganic parts. Main aim of this work was attempt to find relationships beetwen selected physicochemical properties of peats soils and height of the most important infrared bands of these materials. 11 peaty-muck soils were taken from different places in Eastern part of Poland from deph 0-20cm. After homogenizing, selected parameters were determined for all samples. Content of organic carbon was investigated using TOC analyzer (MultiNC 2000, Analityk Jena), water holding capacity indexes were determined via centrifugation/ weighting method proposed by Gawlik, humification index was calculated using colorimetric method proposed by Springer. Infrared spectra were recorded for samples in form of pellets with KBr. Absorbance of the most important bands were measured: carboxylic for COO- as. (1619-1639cm-1), COO- sym. (1383 - 1387cm-1), COOH sym. (1240 - 1266cm-1) and phenolic groups for (~3389-3401cm-1). After this, relationships between all parameters were found. Results showed presence of statistically significant correlation between absorbance of functional groups and organic carbon content. This relation indicated that increase in organic carbon caused increase in functional groups of organic matter. No statistically significant correlation was found for relation of bands height and water holding capacity and humification index. *This work was partly supported by the National Science Centre in Poland, grant No. UMO-2011/03/N/NZ9/04239.

Does the performance of wet granulation and tablet hardness affect the drug dissolution profile of carvedilol in matrix tablets?

PubMed

Košir, Darjan; Ojsteršek, Tadej; Vrečer, Franc

2018-06-14

Wet granulation is mostly used process for manufacturing matrix tablets. Compared to the direct compression method, it allows for a better flow and compressibility properties of compression mixtures. Granulation, including process parameters and tableting, can influence critical quality attributes (CQAs) of hydrophilic matrix tablets. One of the most important CQAs is the drug release profile. We studied the influence of granulation process parameters (type of nozzle and water quantity used as granulation liquid) and tablet hardness on the drug release profile. Matrix tablets contained HPMC K4M hydrophilic matrix former and carvedilol as a model drug. The influence of selected HPMC characteristics on the drug release profile was also evaluated using two additional HPMC batches. For statistical evaluation, partial least square (PLS) models were generated for each time point of the drug release profile using the same number of latent factors. In this way, it was possible to evaluate how the importance of factors influencing drug dissolution changes in dependence on time throughout the drug release profile. The results of statistical evaluation show that the granulation process parameters (granulation liquid quantity and type of nozzle) and tablet hardness significantly influence the release profile. On the other hand, the influence of HPMC characteristics is negligible in comparison to the other factors studied. Using a higher granulation liquid quantity and the standard nozzle type results in larger granules with a higher density and lower porosity, which leads to a slower drug release profile. Lower tablet hardness also slows down the release profile.

Optimisation of warpage on thin shell plastic part using response surface methodology (RSM) and glowworm swarm optimisation (GSO)

NASA Astrophysics Data System (ADS)

Asyirah, B. N.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

In manufacturing a variety of parts, plastic injection moulding is widely use. The injection moulding process parameters have played important role that affects the product's quality and productivity. There are many approaches in minimising the warpage ans shrinkage such as artificial neural network, genetic algorithm, glowworm swarm optimisation and hybrid approaches are addressed. In this paper, a systematic methodology for determining a warpage and shrinkage in injection moulding process especially in thin shell plastic parts are presented. To identify the effects of the machining parameters on the warpage and shrinkage value, response surface methodology is applied. In thos study, a part of electronic night lamp are chosen as the model. Firstly, experimental design were used to determine the injection parameters on warpage for different thickness value. The software used to analyse the warpage is Autodesk Moldflow Insight (AMI) 2012.

Efficient HIK SVM learning for image classification.

PubMed

Wu, Jianxin

2012-10-01

Histograms are used in almost every aspect of image processing and computer vision, from visual descriptors to image representations. Histogram intersection kernel (HIK) and support vector machine (SVM) classifiers are shown to be very effective in dealing with histograms. This paper presents contributions concerning HIK SVM for image classification. First, we propose intersection coordinate descent (ICD), a deterministic and scalable HIK SVM solver. ICD is much faster than, and has similar accuracies to, general purpose SVM solvers and other fast HIK SVM training methods. We also extend ICD to the efficient training of a broader family of kernels. Second, we show an important empirical observation that ICD is not sensitive to the C parameter in SVM, and we provide some theoretical analyses to explain this observation. ICD achieves high accuracies in many problems, using its default parameters. This is an attractive property for practitioners, because many image processing tasks are too large to choose SVM parameters using cross-validation.

Resist process optimization for further defect reduction

NASA Astrophysics Data System (ADS)

Tanaka, Keiichi; Iseki, Tomohiro; Marumoto, Hiroshi; Takayanagi, Koji; Yoshida, Yuichi; Uemura, Ryouichi; Yoshihara, Kosuke

2012-03-01

Defect reduction has become one of the most important technical challenges in device mass-production. Knowing that resist processing on a clean track strongly impacts defect formation in many cases, we have been trying to improve the track process to enhance customer yield. For example, residual type defect and pattern collapse are strongly related to process parameters in developer, and we have reported new develop and rinse methods in the previous papers. Also, we have reported the optimization method of filtration condition to reduce bridge type defects, which are mainly caused by foreign substances such as gels in resist. Even though we have contributed resist caused defect reduction in past studies, defect reduction requirements continue to be very important. In this paper, we will introduce further process improvements in terms of resist defect reduction, including the latest experimental data.

Evolution of quantitative methods for the study and management of avian populations: on the importance of individual contributions

USGS Publications Warehouse

Nichols, J.D.

2004-01-01

The EURING meetings and the scientists who have attended them have contributed substantially to the growth of knowledge in the field of estimating parameters of animal populations. The contributions of David R. Anderson to process modeling, parameter estimation and decision analysis are briefly reviewed. Metrics are considered for assessing individual contributions to a field of inquiry, and it is concluded that Anderson’s contributions have been substantial. Important characteristics of Anderson and his career are the ability to identify and focus on important topics, the premium placed on dissemination of new methods to prospective users, the ability to assemble teams of complementary researchers, and the innovation and vision that characterized so much of his work. The paper concludes with a list of interesting current research topics for consideration by EURING participants.

Discrete element modeling of the mass movement and loose material supplying the gully process of a debris avalanche in the Bayi Gully, Southwest China

NASA Astrophysics Data System (ADS)

Zhou, Jia-wen; Huang, Kang-xin; Shi, Chong; Hao, Ming-hui; Guo, Chao-xu

2015-03-01

The dynamic process of a debris avalanche in mountainous areas is influenced by the landslide volume, topographical conditions, mass-material composition, mechanical properties and other factors. A good understanding of the mass movement and loose material supplying the gully process is very important for understanding the dynamic properties of debris avalanches. Three-dimensional particle flow code (PFC3D) was used to simulate a debris avalanche in Quaternary deposits at the Bayi Gully, Southwest China. FORTRAN and AutoCAD were used for the secondary development to display the mass movement process and to quantitatively describe the mass movement and loose material supplying the gully process. The simulated results show that after the landslide is initiated, the gravitational potential energy is converted into kinetic energy with a variation velocity for the sliding masses. Two stages exist for the average-movement velocity: the acceleration stage and the slowdown stage, which are influenced by the topographical conditions. For the loose materials supplying the gully process, the cumulative volume of the sliding masses into the gully gradually increases over the time. When the landslide volume is not large enough, the increasing landslide volume does not obviously influence the movement process of the sliding masses. The travel distance and movement velocity increase with the decreasing numerical parameters, and the mass-movement process is finished more quickly using low-value parameters. The deposition area of the sliding masses decreases with the increasing numerical parameters and the corresponding deposition thickness increases. The mass movement of the debris avalanche is not only influenced by the mechanical parameters but is also controlled by the topographical conditions.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

PubMed

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other

PubMed Central

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients’ medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD. PMID:28497080

Modelling and intepreting the isotopic composition of water vapour in convective updrafts

NASA Astrophysics Data System (ADS)

Bolot, M.; Legras, B.; Moyer, E. J.

2012-08-01

The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener-Bergeron-Findeisen process). As all of these processes are related to updraft strength, droplet size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

Modelling and interpreting the isotopic composition of water vapour in convective updrafts

NASA Astrophysics Data System (ADS)

Bolot, M.; Legras, B.; Moyer, E. J.

2013-08-01

The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed-phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters, including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener-Bergeron-Findeisen process). As all of these processes are related to updraft strength, particle size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

Groundwater sapping channels: Summary of effects of experiments with varied stratigraphy

NASA Technical Reports Server (NTRS)

Kochel, R. Craig; Simmons, David W.

1987-01-01

Experiments in the recirculating flume sapping box have modeled valley formation by groundwater sapping processes in a number of settings. The effects of the following parameters on sapping channel morphology were examined: surface slope; stratigraphic variations in permeability cohesion and dip; and structure of joints and dikes. These kinds of modeling experiments are particularly good for: testing concepts; developing a suite of distinctive morphologies and morphometries indicative of sapping; helping to relate process to morphology; and providing data necessary to assess the relative importance of runoff, sapping, and mass wasting processes on channel development. The observations from the flume systems can be used to help interpret features observed in terrestrial and Martian settings where sapping processes are thought to have played an important role in the development of valley networks.

Double-layer optical fiber coating analysis in MHD flow of an elastico-viscous fluid using wet-on-wet coating process

NASA Astrophysics Data System (ADS)

Khan, Zeeshan; Islam, Saeed; Shah, Rehan Ali; Khan, Muhammad Altaf; Bonyah, Ebenezer; Jan, Bilal; Khan, Aurangzeb

Modern optical fibers require a double-layer coating on the glass fiber in order to provide protection from signal attenuation and mechanical damage. The most important plastic resins used in wires and optical fibers are plastic polyvinyl chloride (PVC) and low and high density polyethylene (LDPE/HDPE), nylon and Polysulfone. One of the most important things which affect the final product after processing is the design of the coating die. In the present study, double-layer optical fiber coating is performed using melt polymer satisfying Oldroyd 8-constant fluid model in a pressure type die with the effect of magneto-hydrodynamic (MHD). Wet-on-wet coating process is applied for double-layer optical fiber coating. The coating process in the coating die is modeled as a simple two-layer Couette flow of two immiscible fluids in an annulus with an assigned pressure gradient. Based on the assumptions of fully developed laminar and MHD flow, the Oldroyd 8-constant model of non-Newtonian fluid of two immiscible resin layers is modeled. The governing nonlinear equations are solved analytically by the new technique of Optimal Homotopy Asymptotic Method (OHAM). The convergence of the series solution is established. The results are also verified by the Adomian Decomposition Method (ADM). The effect of important parameters such as magnetic parameter Mi , the dilatant constant α , the Pseodoplastic constant β , the radii ratio δ , the pressure gradient Ω , the speed of fiber optics V , and the viscosity ratio κ on the velocity profiles, thickness of coated fiber optics, volume flow rate, and shear stress on the fiber optics are investigated. At the end the result of the present work is also compared with the experimental results already available in the literature by taking non-Newtonian parameters tends to zero.

Optical and mechanical nondestructive tests for measuring tomato fruit firmness

NASA Astrophysics Data System (ADS)

Manivel-Chávez, Ricardo A.; Garnica-Romo, M. G.; Arroyo-Correa, Gabriel; Aranda-Sánchez, Jorge I.

2011-08-01

Ripening is one of the most important processes to occur in fruits which involve changes in color, flavor, and texture. An important goal in quality control of fruits is to substitute traditional sensory testing methods with reliable nondestructive tests (NDT). In this work we study the firmness of tomato fruits by using optical and mechanical NDT. Optical and mechanical parameters, measured along the tomato shelf life, are shown.

Digital image processing based identification of nodes and internodes of chopped biomass stems

USDA-ARS?s Scientific Manuscript database

Chemical composition of biomass feedstock is an important parameter for optimizing the yield and economics of various bioconversion pathways. Although understandably, the chemical composition of biomass varies among species, varieties, and plant components, there is distinct variation even among ste...

Fuzzy simulation in concurrent engineering

NASA Technical Reports Server (NTRS)

Kraslawski, A.; Nystrom, L.

1992-01-01

Concurrent engineering is becoming a very important practice in manufacturing. A problem in concurrent engineering is the uncertainty associated with the values of the input variables and operating conditions. The problem discussed in this paper concerns the simulation of processes where the raw materials and the operational parameters possess fuzzy characteristics. The processing of fuzzy input information is performed by the vertex method and the commercial simulation packages POLYMATH and GEMS. The examples are presented to illustrate the usefulness of the method in the simulation of chemical engineering processes.

Simulation of salt production process

NASA Astrophysics Data System (ADS)

Muraveva, E. A.

2017-10-01

In this paper an approach to the use of simulation software iThink to simulate the salt production system has been proposed. The dynamic processes of the original system are substituted by processes simulated in the abstract model, but in compliance with the basic rules of the original system, which allows one to accelerate and reduce the cost of the research. As a result, a stable workable simulation model was obtained that can display the rate of the salt exhaustion and many other parameters which are important for business planning.

Parametric uncertainties in global model simulations of black carbon column mass concentration

NASA Astrophysics Data System (ADS)

Pearce, Hana; Lee, Lindsay; Reddington, Carly; Carslaw, Ken; Mann, Graham

2016-04-01

Previous studies have deduced that the annual mean direct radiative forcing from black carbon (BC) aerosol may regionally be up to 5 W m-2 larger than expected due to underestimation of global atmospheric BC absorption in models. We have identified the magnitude and important sources of parametric uncertainty in simulations of BC column mass concentration from a global aerosol microphysics model (GLOMAP-Mode). A variance-based uncertainty analysis of 28 parameters has been performed, based on statistical emulators trained on model output from GLOMAP-Mode. This is the largest number of uncertain model parameters to be considered in a BC uncertainty analysis to date and covers primary aerosol emissions, microphysical processes and structural parameters related to the aerosol size distribution. We will present several recommendations for further research to improve the fidelity of simulated BC. In brief, we find that the standard deviation around the simulated mean annual BC column mass concentration varies globally between 2.5 x 10-9 g cm-2 in remote marine regions and 1.25 x 10-6 g cm-2 near emission sources due to parameter uncertainty Between 60 and 90% of the variance over source regions is due to uncertainty associated with primary BC emission fluxes, including biomass burning, fossil fuel and biofuel emissions. While the contributions to BC column uncertainty from microphysical processes, for example those related to dry and wet deposition, are increased over remote regions, we find that emissions still make an important contribution in these areas. It is likely, however, that the importance of structural model error, i.e. differences between models, is greater than parametric uncertainty. We have extended our analysis to emulate vertical BC profiles at several locations in the mid-Pacific Ocean and identify the parameters contributing to uncertainty in the vertical distribution of black carbon at these locations. We will present preliminary comparisons of emulated BC vertical profiles from the AeroCom multi-model ensemble and Hiaper Pole-to-Pole (HIPPO) observations.

Effect of Ga incorporation on morphology and defect structures evolution in VLS grown 1D In2O3 nanostructures

NASA Astrophysics Data System (ADS)

Ramos-Ramón, Jesús Alberto; Pal, Umapada; Cremades, Ana; Maestre, David

2018-05-01

Fabrication of 1D metal oxide nanostructures of controlled morphology and defect structure is of immense importance for their application in optoelectronics. While the morphology of these nanostructures depends primarily on growth parameters utilized in physical deposition processes, incorporation of foreign elements or dopants not only affects their morphology, but also affects their crystallinity and defect structure, which are the most important parameters for their device applications. Herein we report on the growth of highly crystalline 1D In2O3 nanostructures through vapor-liquid-solid process at relatively low temperature, and the effect of Ga incorporation on their morphology and defect structures. Through electron microscopy, Raman spectroscopy and cathodoluminescence spectroscopy techniques, we demonstrate that incorporation of Ga in In2O3 nanostructures not only strongly affects their morphology, but also generates new defect levels in the band gap of In2O3, shifting the overall emission of the nanostructures towards visible spectral range.

Automated system for generation of soil moisture products for agricultural drought assessment

NASA Astrophysics Data System (ADS)

Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.

2014-11-01

Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically download requisite input parameters like rainfall, Potential Evapotranspiration (PET) from respective servers. It can import file formats like .grd, .hdf, .img, generic binary etc, perform geometric correction and re-project the files to native projection system. The software takes into account the weather, crop and soil parameters to run the designed soil water balance model. The software also has additional features like time compositing of outputs to generate weekly, fortnightly profiles for further analysis. Other tools to generate "Area Favorable for Crop Sowing" using the daily soil moisture with highly customizable parameters interface has been provided. A whole India analysis would now take a mere 20 seconds for generation of soil moisture products which would normally take one hour per day using commercial software.

Introducing uncertainty analysis of nucleation and crystal growth models in Process Analytical Technology (PAT) system design of crystallization processes.

PubMed

Samad, Noor Asma Fazli Abdul; Sin, Gürkan; Gernaey, Krist V; Gani, Rafiqul

2013-11-01

This paper presents the application of uncertainty and sensitivity analysis as part of a systematic model-based process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty, while for sensitivity analysis, global methods including the standardized regression coefficients (SRC) and Morris screening are used to identify the most significant parameters. The potassium dihydrogen phosphate (KDP) crystallization process is used as a case study, both in open-loop and closed-loop operation. In the uncertainty analysis, the impact on the predicted output of uncertain parameters related to the nucleation and the crystal growth model has been investigated for both a one- and two-dimensional crystal size distribution (CSD). The open-loop results show that the input uncertainties lead to significant uncertainties on the CSD, with appearance of a secondary peak due to secondary nucleation for both cases. The sensitivity analysis indicated that the most important parameters affecting the CSDs are nucleation order and growth order constants. In the proposed PAT system design (closed-loop), the target CSD variability was successfully reduced compared to the open-loop case, also when considering uncertainty in nucleation and crystal growth model parameters. The latter forms a strong indication of the robustness of the proposed PAT system design in achieving the target CSD and encourages its transfer to full-scale implementation. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for improving the model physics parameterizations.

Selected algorithms for measurement data processing in impulse-radar-based system for monitoring of human movements

NASA Astrophysics Data System (ADS)

Miękina, Andrzej; Wagner, Jakub; Mazurek, Paweł; Morawski, Roman Z.

2016-11-01

The importance of research on new technologies that could be employed in care services for elderly and disabled persons is highlighted. Advantages of impulse-radar sensors, when applied for non-intrusive monitoring of such persons in their home environment, are indicated. Selected algorithms for the measurement data preprocessing - viz. the algorithms for clutter suppression and echo parameter estimation, as well as for estimation of the twodimensional position of a monitored person - are proposed. The capability of an impulse-radar- based system to provide some application-specific parameters, viz. the parameters characterising the patient's health condition, is also demonstrated.

Application of experimental design in geothermal resources assessment of Ciwidey-Patuha, West Java, Indonesia

NASA Astrophysics Data System (ADS)

Ashat, Ali; Pratama, Heru Berian

2017-12-01

The successful Ciwidey-Patuha geothermal field size assessment required integration data analysis of all aspects to determined optimum capacity to be installed. Resources assessment involve significant uncertainty of subsurface information and multiple development scenarios from these field. Therefore, this paper applied the application of experimental design approach to the geothermal numerical simulation of Ciwidey-Patuha to generate probabilistic resource assessment result. This process assesses the impact of evaluated parameters affecting resources and interacting between these parameters. This methodology have been successfully estimated the maximum resources with polynomial function covering the entire range of possible values of important reservoir parameters.

Effects of implant drilling parameters for pilot and twist drills on temperature rise in bone analog and alveolar bones.

PubMed

Chen, Yung-Chuan; Hsiao, Chih-Kun; Ciou, Ji-Sih; Tsai, Yi-Jung; Tu, Yuan-Kun

2016-11-01

This study concerns the effects of different drilling parameters of pilot drills and twist drills on the temperature rise of alveolar bones during dental implant procedures. The drilling parameters studied here include the feed rate and rotation speed of the drill. The bone temperature distribution was analyzed through experiments and numerical simulations of the drilling process. In this study, a three dimensional (3D) elasto-plastic dynamic finite element model (DFEM) was proposed to investigate the effects of drilling parameters on the bone temperature rise. In addition, the FE model is validated with drilling experiments on artificial human bones and porcine alveolar bones. The results indicate that 3D DFEM can effectively simulate the bone temperature rise during the drilling process. During the drilling process with pilot drills or twist drills, the maximum bone temperature occurred in the region of the cancellous bones close to the cortical bones. The feed rate was one of the important factors affecting the time when the maximum bone temperature occurred. Our results also demonstrate that the elevation of bone temperature was reduced as the feed rate increased and the drill speed decreased, which also effectively reduced the risk region of osteonecrosis. These findings can serve as a reference for dentists in choosing drilling parameters for dental implant surgeries. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Optimization of process parameters of pulsed TIG welded maraging steel C300

NASA Astrophysics Data System (ADS)

Deepak, P.; Jualeash, M. J.; Jishnu, J.; Srinivasan, P.; Arivarasu, M.; Padmanaban, R.; Thirumalini, S.

2016-09-01

Pulsed TIG welding technology provides excellent welding performance on thin sections which helps to increase productivity, enhance weld quality, minimize weld costs, and boost operator efficiency and this has drawn the attention of the welding society. Maraging C300 steel is extensively used in defence and aerospace industry and thus its welding becomes an area of paramount importance. In pulsed TIG welding, weld quality depends on the process parameters used. In this work, Pulsed TIG bead-on-plate welding is performed on a 5mm thick maraging C300 plate at different combinations of input parameters: peak current (Ip), base current (Ib) and pulsing frequency (HZ) as per box behnken design with three-levels for each factor. Response surface methodology is utilized for establishing a mathematical model for predicting the weld bead depth. The effect of Ip, Ib and HZ on the weld bead depth is investigated using the developed model. The weld bead depth is found to be affected by all the three parameters. Surface and contour plots developed from regression equation are used to optimize the processing parameters for maximizing the weld bead depth. Optimum values of Ip, Ib and HZ are obtained as 259 A, 120 A and 8 Hz respectively. Using this optimum condition, maximum bead depth of the weld is predicted to be 4.325 mm.

Group Contribution Methods for Phase Equilibrium Calculations.

PubMed

Gmehling, Jürgen; Constantinescu, Dana; Schmid, Bastian

2015-01-01

The development and design of chemical processes are carried out by solving the balance equations of a mathematical model for sections of or the whole chemical plant with the help of process simulators. For process simulation, besides kinetic data for the chemical reaction, various pure component and mixture properties are required. Because of the great importance of separation processes for a chemical plant in particular, a reliable knowledge of the phase equilibrium behavior is required. The phase equilibrium behavior can be calculated with the help of modern equations of state or g(E)-models using only binary parameters. But unfortunately, only a very small part of the experimental data for fitting the required binary model parameters is available, so very often these models cannot be applied directly. To solve this problem, powerful predictive thermodynamic models have been developed. Group contribution methods allow the prediction of the required phase equilibrium data using only a limited number of group interaction parameters. A prerequisite for fitting the required group interaction parameters is a comprehensive database. That is why for the development of powerful group contribution methods almost all published pure component properties, phase equilibrium data, excess properties, etc., were stored in computerized form in the Dortmund Data Bank. In this review, the present status, weaknesses, advantages and disadvantages, possible applications, and typical results of the different group contribution methods for the calculation of phase equilibria are presented.

Volcanic Ash Data Assimilation System for Atmospheric Transport Model

NASA Astrophysics Data System (ADS)

Ishii, K.; Shimbori, T.; Sato, E.; Tokumoto, T.; Hayashi, Y.; Hashimoto, A.

2017-12-01

The Japan Meteorological Agency (JMA) has two operations for volcanic ash forecasts, which are Volcanic Ash Fall Forecast (VAFF) and Volcanic Ash Advisory (VAA). In these operations, the forecasts are calculated by atmospheric transport models including the advection process, the turbulent diffusion process, the gravitational fall process and the deposition process (wet/dry). The initial distribution of volcanic ash in the models is the most important but uncertain factor. In operations, the model of Suzuki (1983) with many empirical assumptions is adopted to the initial distribution. This adversely affects the reconstruction of actual eruption plumes.We are developing a volcanic ash data assimilation system using weather radars and meteorological satellite observation, in order to improve the initial distribution of the atmospheric transport models. Our data assimilation system is based on the three-dimensional variational data assimilation method (3D-Var). Analysis variables are ash concentration and size distribution parameters which are mutually independent. The radar observation is expected to provide three-dimensional parameters such as ash concentration and parameters of ash particle size distribution. On the other hand, the satellite observation is anticipated to provide two-dimensional parameters of ash clouds such as mass loading, top height and particle effective radius. In this study, we estimate the thickness of ash clouds using vertical wind shear of JMA numerical weather prediction, and apply for the volcanic ash data assimilation system.

Honing process optimization algorithms

NASA Astrophysics Data System (ADS)

Kadyrov, Ramil R.; Charikov, Pavel N.; Pryanichnikova, Valeria V.

2018-03-01

This article considers the relevance of honing processes for creating high-quality mechanical engineering products. The features of the honing process are revealed and such important concepts as the task for optimization of honing operations, the optimal structure of the honing working cycles, stepped and stepless honing cycles, simulation of processing and its purpose are emphasized. It is noted that the reliability of the mathematical model determines the quality parameters of the honing process control. An algorithm for continuous control of the honing process is proposed. The process model reliably describes the machining of a workpiece in a sufficiently wide area and can be used to operate the CNC machine CC743.

Simulation and design of ECT differential bobbin probes for the inspection of cracks in bolts

NASA Astrophysics Data System (ADS)

Ra, S. W.; Im, K. H.; Lee, S. G.; Kim, H. J.; Song, S. J.; Kim, S. K.; Cho, Y. T.; Woo, Y. D.; Jung, J. A.

2015-12-01

All Various defects could be generated in bolts for a use of oil filters for the manufacturing process and then may affect to the safety and quality in bolts. Also, fine defects may be imbedded in oil filter system during multiple forging manufacturing processes. So it is very important that such defects be investigated and screened during the multiple manufacturing processes. Therefore, in order effectively to evaluate the fine defects, the design parameters for bobbin-types were selected under a finite element method (FEM) simulations and Eddy current testing (ECT). Especially the FEM simulations were performed to make characterization in the crack detection of the bolts and the parameters such as number of turns of the coil, the coil size and applied frequency were calculated based on the simulation results.

Design Space Approach in Optimization of Fluid Bed Granulation and Tablets Compression Process

PubMed Central

Djuriš, Jelena; Medarević, Djordje; Krstić, Marko; Vasiljević, Ivana; Mašić, Ivana; Ibrić, Svetlana

2012-01-01

The aim of this study was to optimize fluid bed granulation and tablets compression processes using design space approach. Type of diluent, binder concentration, temperature during mixing, granulation and drying, spray rate, and atomization pressure were recognized as critical formulation and process parameters. They were varied in the first set of experiments in order to estimate their influences on critical quality attributes, that is, granules characteristics (size distribution, flowability, bulk density, tapped density, Carr's index, Hausner's ratio, and moisture content) using Plackett-Burman experimental design. Type of diluent and atomization pressure were selected as the most important parameters. In the second set of experiments, design space for process parameters (atomization pressure and compression force) and its influence on tablets characteristics was developed. Percent of paracetamol released and tablets hardness were determined as critical quality attributes. Artificial neural networks (ANNs) were applied in order to determine design space. ANNs models showed that atomization pressure influences mostly on the dissolution profile, whereas compression force affects mainly the tablets hardness. Based on the obtained ANNs models, it is possible to predict tablet hardness and paracetamol release profile for any combination of analyzed factors. PMID:22919295

The impact of semen processing on sperm parameters and pregnancy rates after intrauterine insemination.

PubMed

Ruiter-Ligeti, Jacob; Agbo, Chioma; Dahan, Michael

2017-06-01

The objective of this retrospective study was to evaluate the effect of semen processing on computer analyzed semen parameters and pregnancy rates after intrauterine insemination (IUI). Over a two-year period, a total of 981 couples undergoing 2231 IUI cycles were evaluated and the freshly collected non-donor semen was analyzed before and after density gradient centrifugation (DGC). DGC led to significant increases in sperm concentration by 66±74 ×106/mL (P=0.0001), percentage of motile sperm by 24±22% (P=0.0001), concentration motile by 27±58 ×106/mL (P=0.0001), and forward sperm progression by 18±14 µ/s (P=0.0001). In 95% of cases, there was a decrease in the total motile sperm count (TMSC), with an average decrease of 50±124% compared to pre-processed samples (P=0.0001). Importantly, the decrease in TMSC did not negatively affect pregnancy rates (P=0.45). This study proves that DGC leads to significant increases in most sperm parameters, with the exception of TMSC. Remarkably, the decrease in TMSC did not affect the pregnancy rate. This should reassure clinicians when the TMSC is negatively affected by processing.

An advanced technique for the prediction of decelerator system dynamics.

NASA Technical Reports Server (NTRS)

Talay, T. A.; Morris, W. D.; Whitlock, C. H.

1973-01-01

An advanced two-body six-degree-of-freedom computer model employing an indeterminate structures approach has been developed for the parachute deployment process. The program determines both vehicular and decelerator responses to aerodynamic and physical property inputs. A better insight into the dynamic processes that occur during parachute deployment has been developed. The model is of value in sensitivity studies to isolate important parameters that affect the vehicular response.

Optimisation of shock absorber process parameters using failure mode and effect analysis and genetic algorithm

NASA Astrophysics Data System (ADS)

Mariajayaprakash, Arokiasamy; Senthilvelan, Thiyagarajan; Vivekananthan, Krishnapillai Ponnambal

2013-07-01

The various process parameters affecting the quality characteristics of the shock absorber during the process were identified using the Ishikawa diagram and by failure mode and effect analysis. The identified process parameters are welding process parameters (squeeze, heat control, wheel speed, and air pressure), damper sealing process parameters (load, hydraulic pressure, air pressure, and fixture height), washing process parameters (total alkalinity, temperature, pH value of rinsing water, and timing), and painting process parameters (flowability, coating thickness, pointage, and temperature). In this paper, the process parameters, namely, painting and washing process parameters, are optimized by Taguchi method. Though the defects are reasonably minimized by Taguchi method, in order to achieve zero defects during the processes, genetic algorithm technique is applied on the optimized parameters obtained by Taguchi method.

Study of Material Consolidation at Higher Throughput Parameters in Selective Laser Melting of Inconel 718

NASA Technical Reports Server (NTRS)

Prater, Tracie

2016-01-01

Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. SLM stands poised to revolutionize propulsion manufacturing, but there are a number of technical questions that must be addressed in order to achieve rapid, efficient fabrication and ensure adequate performance of parts manufactured using this process in safety-critical flight applications. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this work is to characterize the impact of higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. In phase I of this work, density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, hatch spacing, and layer thickness) and material consolidation (assessed in terms of as-built density and porosity). Phase II additionally considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the same higher energy parameter regime considered in the phase I work. Density and microstructure represent the "first-gate" metrics for determining the adequacy of the SLM process in this parameter range and, as a critical initial indicator of material quality, will factor into a follow-on DOE that assesses the impact of these parameters on mechanical properties. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

LCE: leaf carbon exchange data set for tropical, temperate, and boreal species of North and Central America.

PubMed

Smith, Nicholas G; Dukes, Jeffrey S

2017-11-01

Leaf canopy carbon exchange processes, such as photosynthesis and respiration, are substantial components of the global carbon cycle. Climate models base their simulations of photosynthesis and respiration on an empirical understanding of the underlying biochemical processes, and the responses of those processes to environmental drivers. As such, data spanning large spatial scales are needed to evaluate and parameterize these models. Here, we present data on four important biochemical parameters defining leaf carbon exchange processes from 626 individuals of 98 species at 12 North and Central American sites spanning ~53° of latitude. The four parameters are the maximum rate of Rubisco carboxylation (V cmax ), the maximum rate of electron transport for the regeneration of Ribulose-1,5,-bisphosphate (J max ), the maximum rate of phosphoenolpyruvate carboxylase carboxylation (V pmax ), and leaf dark respiration (R d ). The raw net photosynthesis by intercellular CO 2 (A/C i ) data used to calculate V cmax , J max , and V pmax rates are also presented. Data were gathered on the same leaf of each individual (one leaf per individual), allowing for the examination of each parameter relative to others. Additionally, the data set contains a number of covariates for the plants measured. Covariate data include (1) leaf-level traits (leaf mass, leaf area, leaf nitrogen and carbon content, predawn leaf water potential), (2) plant-level traits (plant height for herbaceous individuals and diameter at breast height for trees), (3) soil moisture at the time of measurement, (4) air temperature from nearby weather stations for the day of measurement and each of the 90 d prior to measurement, and (5) climate data (growing season mean temperature, precipitation, photosynthetically active radiation, vapor pressure deficit, and aridity index). We hope that the data will be useful for obtaining greater understanding of the abiotic and biotic determinants of these important biochemical parameters and for evaluating and improving large-scale models of leaf carbon exchange. © 2017 by the Ecological Society of America.

Development of a controlled release formulation by continuous twin screw granulation: Influence of process and formulation parameters.

PubMed

Vanhoorne, V; Vanbillemont, B; Vercruysse, J; De Leersnyder, F; Gomes, P; Beer, T De; Remon, J P; Vervaet, C

2016-05-30

The aim of this study was to evaluate the potential of twin screw granulation for the continuous production of controlled release formulations with hydroxypropylmethylcellulose as hydrophilic matrix former. Metoprolol tartrate was included in the formulation as very water soluble model drug. A premix of metoprolol tartrate, hydroxypropylmethylcellulose and filler (ratio 20/20/60, w/w) was granulated with demineralized water via twin screw granulation. After oven drying and milling, tablets were produced on a rotary Modul™ P tablet press. A D-optimal design (29 experiments) was used to assess the influence of process (screw speed, throughput, barrel temperature and screw design) and formulation parameters (starch content of the filler) on the process (torque), granule (size distribution, shape, friability, density) and tablet (hardness, friability and dissolution) critical quality attributes. The torque was dominated by the number of kneading elements and throughput, whereas screw speed and filling degree only showed a minor influence on torque. Addition of screw mixing elements after a block of kneading elements improved the yield of the process before milling as it resulted in less oversized granules and also after milling as less fines were present. Temperature was also an important parameter to optimize as a higher temperature yielded less fines and positively influenced the aspect ratio. The shape of hydroxypropylmethylcellulose granules was comparable to that of immediate release formulations. Tensile strength and friability of tablets were not dependent on the process parameters. The use of starch as filler was not beneficial with regard to granule and tablet properties. Complete drug release was obtained after 16-20h and was independent of the design's parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

Relating memory to functional performance in normal aging to dementia using hierarchical Bayesian cognitive processing models.

PubMed

Shankle, William R; Pooley, James P; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D

2013-01-01

Determining how cognition affects functional abilities is important in Alzheimer disease and related disorders. A total of 280 patients (normal or Alzheimer disease and related disorders) received a total of 1514 assessments using the functional assessment staging test (FAST) procedure and the MCI Screen. A hierarchical Bayesian cognitive processing model was created by embedding a signal detection theory model of the MCI Screen-delayed recognition memory task into a hierarchical Bayesian framework. The signal detection theory model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the 6 FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. Hierarchical Bayesian cognitive processing models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition into a continuous measure of functional severity for both individuals and FAST groups. Such a translation links 2 levels of brain information processing and may enable more accurate correlations with other levels, such as those characterized by biomarkers.

Estimation of the viscosities of liquid binary alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Su, Xiang-Yu

2018-01-01

As one of the most important physical and chemical properties, viscosity plays a critical role in physics and materials as a key parameter to quantitatively understanding the fluid transport process and reaction kinetics in metallurgical process design. Experimental and theoretical studies on liquid metals are problematic. Today, there are many empirical and semi-empirical models available with which to evaluate the viscosity of liquid metals and alloys. However, the parameter of mixed energy in these models is not easily determined, and most predictive models have been poorly applied. In the present study, a new thermodynamic parameter Δ G is proposed to predict liquid alloy viscosity. The prediction equation depends on basic physical and thermodynamic parameters, namely density, melting temperature, absolute atomic mass, electro-negativity, electron density, molar volume, Pauling radius, and mixing enthalpy. Our results show that the liquid alloy viscosity predicted using the proposed model is closely in line with the experimental values. In addition, if the component radius difference is greater than 0.03 nm at a certain temperature, the atomic size factor has a significant effect on the interaction of the binary liquid metal atoms. The proposed thermodynamic parameter Δ G also facilitates the study of other physical properties of liquid metals.

Approach to in-process tool wear monitoring in drilling: Application of Kalman filter theory

NASA Astrophysics Data System (ADS)

He, Ning; Zhang, Youzhen; Pan, Liangxian

1993-05-01

The two parameters often used in adaptive control, tool wear and wear rate, are the important factors affecting machinability. In this paper, it is attempted to use the modern cybernetics to solve the in-process tool wear monitoring problem by applying the Kalman filter theory to monitor drill wear quantitatively. Based on the experimental results, a dynamic model, a measuring model and a measurement conversion model suitable for Kalman filter are established. It is proved that the monitoring system possesses complete observability but does not possess complete controllability. A discriminant for selecting the characteristic parameters is put forward. The thrust force Fz is selected as the characteristic parameter in monitoring the tool wear by this discriminant. The in-process Kalman filter drill wear monitoring system composed of force sensor microphotography and microcomputer is well established. The results obtained by the Kalman filter, the common indirect measuring method and the real drill wear measured by the aid of microphotography are compared. The result shows that the Kalman filter has high precision of measurement and the real time requirement can be satisfied.

wsacrvpthrc.a1

DOE Data Explorer

Gaustad, Krista; Hardin, Joseph

2015-12-14

The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.

wsacrppivh.a1

DOE Data Explorer

Gaustad, Krista; Hardin, Joseph

2015-07-22

The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.

wsacrzrhiv.a1

DOE Data Explorer

Gaustad, Krista; Hardin, Joseph

2015-07-22

The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.

kasacrvpthrc.a1

DOE Data Explorer

Gaustad, Krista; Hardin, Joseph

2015-07-22

The kasacr PCM process executed by the sacr3 binary reads in kasacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.

Optimization and Simulation of Plastic Injection Process using Genetic Algorithm and Moldflow

NASA Astrophysics Data System (ADS)

Martowibowo, Sigit Yoewono; Kaswadi, Agung

2017-03-01

The use of plastic-based products is continuously increasing. The increasing demands for thinner products, lower production costs, yet higher product quality has triggered an increase in the number of research projects on plastic molding processes. An important branch of such research is focused on mold cooling system. Conventional cooling systems are most widely used because they are easy to make by using conventional machining processes. However, the non-uniform cooling processes are considered as one of their weaknesses. Apart from the conventional systems, there are also conformal cooling systems that are designed for faster and more uniform plastic mold cooling. In this study, the conformal cooling system is applied for the production of bowl-shaped product made of PP AZ564. Optimization is conducted to initiate machine setup parameters, namely, the melting temperature, injection pressure, holding pressure and holding time. The genetic algorithm method and Moldflow were used to optimize the injection process parameters at a minimum cycle time. It is found that, an optimum injection molding processes could be obtained by setting the parameters to the following values: T M = 180 °C; P inj = 20 MPa; P hold = 16 MPa and t hold = 8 s, with a cycle time of 14.11 s. Experiments using the conformal cooling system yielded an average cycle time of 14.19 s. The studied conformal cooling system yielded a volumetric shrinkage of 5.61% and the wall shear stress was found at 0.17 MPa. The difference between the cycle time obtained through simulations and experiments using the conformal cooling system was insignificant (below 1%). Thus, combining process parameters optimization and simulations by using genetic algorithm method with Moldflow can be considered as valid.

An actual load forecasting methodology by interval grey modeling based on the fractional calculus.

PubMed

Yang, Yang; Xue, Dingyü

2017-07-17

The operation processes for thermal power plant are measured by the real-time data, and a large number of historical interval data can be obtained from the dataset. Within defined periods of time, the interval information could provide important information for decision making and equipment maintenance. Actual load is one of the most important parameters, and the trends hidden in the historical data will show the overall operation status of the equipments. However, based on the interval grey parameter numbers, the modeling and prediction process is more complicated than the one with real numbers. In order not lose any information, the geometric coordinate features are used by the coordinates of area and middle point lines in this paper, which are proved with the same information as the original interval data. The grey prediction model for interval grey number by the fractional-order accumulation calculus is proposed. Compared with integer-order model, the proposed method could have more freedom with better performance for modeling and prediction, which can be widely used in the modeling process and prediction for the small amount interval historical industry sequence samples. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Capillary electrophoretic study of dibasic acids of different structures: Relation to separation of oxidative intermediates in remediation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Z.; Cocke, D.L.

Dicarboxylic acids are important in environmental chemistry because they are intermediates in oxidative processes involved in natural remediation and waste management processes such as oxidative detoxification and advanced oxidation. Capillary electrophoresis (CE), a promising technique for separating and analyzing these intermediates, has been used to examine a series of dibasic acids of different structures and conformations. This series includes malonic acid, succinic acid, glutaric acid, adipic acid, pimelic acid, maleic acid, fumaric acid, phthalic acid, and trans, trans-muconic acid. The CE parameters as well as structural variations (molecular structure and molecular isomers, buffer composition, pH, applied voltage, injection mode, current,more » temperature, and detection wavelength) that affect the separations and analytical results have been examined in this study. Those factors that affect the separation have been delineated. Among these parameters, the pH has been found to be the most important, which affects the double-layer of the capillary wall, the electro-osmotic flow and analyte mobility. The optimum pH for separating these dibasic acids, as well as the other parameters are discussed in detail and related to the development of methods for analyzing oxidation intermediates in oxidative waste management procedures.« less

Environmental, Human Health and Socio-Economic Effects of Cement Powders: The Multicriteria Analysis as Decisional Methodology

PubMed Central

Moretti, Laura; Di Mascio, Paola; Bellagamba, Simona

2017-01-01

The attention to sustainability-related issues has grown fast in recent decades. The experience gained with these themes reveals the importance of considering this topic in the construction industry, which represents an important sector throughout the world. This work consists on conducting a multicriteria analysis of four cement powders, with the objective of calculating and analysing the environmental, human health and socio-economic effects of their production processes. The economic, technical, environmental and safety performances of the examined powders result from official, both internal and public, documents prepared by the producers. The Analytic Hierarchy Process permitted to consider several indicators (i.e., environmental, human health related and socio-economic parameters) and to conduct comprehensive and unbiased analyses which gave the best, most sustainable cement powder. As assumed in this study, the contribution of each considered parameter to the overall sustainability has a different incidence, therefore the procedure could be used to support on-going sustainability efforts under different conditions. The results also prove that it is not appropriate to regard only one parameter to identify the ‘best’ cement powder, but several impact categories should be considered and analysed if there is an interest for pursuing different, often conflicting interests. PMID:28621754

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

Comparing methods for Earthquake Location

NASA Astrophysics Data System (ADS)

Turkaya, Semih; Bodin, Thomas; Sylvander, Matthieu; Parroucau, Pierre; Manchuel, Kevin

2017-04-01

There are plenty of methods available for locating small magnitude point source earthquakes. However, it is known that these different approaches produce different results. For each approach, results also depend on a number of parameters which can be separated into two main branches: (1) parameters related to observations (number and distribution of for example) and (2) parameters related to the inversion process (velocity model, weighting parameters, initial location etc.). Currently, the results obtained from most of the location methods do not systematically include quantitative uncertainties. The effect of the selected parameters on location uncertainties is also poorly known. Understanding the importance of these different parameters and their effect on uncertainties is clearly required to better constrained knowledge on fault geometry, seismotectonic processes and at the end to improve seismic hazard assessment. In this work, realized in the frame of the SINAPS@ research program (http://www.institut-seism.fr/projets/sinaps/), we analyse the effect of different parameters on earthquakes location (e.g. type of phase, max. hypocentral separation etc.). We compare several codes available (Hypo71, HypoDD, NonLinLoc etc.) and determine their strengths and weaknesses in different cases by means of synthetic tests. The work, performed for the moment on synthetic data, is planned to be applied, in a second step, on data collected by the Midi-Pyrénées Observatory (OMP).

Development of an inexpensive optical method for studies of dental erosion process in vitro

NASA Astrophysics Data System (ADS)

Nasution, A. M. T.; Noerjanto, B.; Triwanto, L.

2008-09-01

Teeth have important roles in digestion of food, supporting the facial-structure, as well as in articulation of speech. Abnormality in teeth structure can be initiated by an erosion process due to diet or beverages consumption that lead to destruction which affect their functionality. Research to study the erosion processes that lead to teeth's abnormality is important in order to be used as a care and prevention purpose. Accurate measurement methods would be necessary as a research tool, in order to be capable for quantifying dental destruction's degree. In this work an inexpensive optical method as tool to study dental erosion process is developed. It is based on extraction the parameters from the 3D dental visual information. The 3D visual image is obtained from reconstruction of multiple lateral projection of 2D images that captured from many angles. Using a simple motor stepper and a pocket digital camera, sequence of multi-projection 2D images of premolar tooth is obtained. This images are then reconstructed to produce a 3D image, which is useful for quantifying related dental erosion parameters. The quantification process is obtained from the shrinkage of dental volume as well as surface properties due to erosion process. Results of quantification is correlated to the ones of dissolved calcium atom which released from the tooth using atomic absorption spectrometry. This proposed method would be useful as visualization tool in many engineering, dentistry, and medical research. It would be useful also for the educational purposes.

Determination of thermodynamic and transport parameters of naphthenic acids and organic process chemicals in oil sand tailings pond water.

PubMed

Wang, Xiaomeng; Robinson, Lisa; Wen, Qing; Kasperski, Kim L

2013-07-01

Oil sand tailings pond water contains naphthenic acids and process chemicals (e.g., alkyl sulphates, quaternary ammonium compounds, and alkylphenol ethoxylates). These chemicals are toxic and can seep through the foundation of the tailings pond to the subsurface, potentially affecting the quality of groundwater. As a result, it is important to measure the thermodynamic and transport parameters of these chemicals in order to study the transport behavior of contaminants through the foundation as well as underground. In this study, batch adsorption studies and column experiments were performed. It was found that the transport parameters of these chemicals are related to their molecular structures and other properties. The computer program (CXTFIT) was used to further evaluate the transport process in the column experiments. The results from this study show that the transport of naphthenic acids in a glass column is an equilibrium process while the transport of process chemicals seems to be a non-equilibrium process. At the end of this paper we present a real-world case study in which the transport of the contaminants through the foundation of an external tailings pond is calculated using the lab-measured data. The results show that long-term groundwater monitoring of contaminant transport at the oil sand mining site may be necessary to avoid chemicals from reaching any nearby receptors.

a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset

NASA Astrophysics Data System (ADS)

Zhou, Y. K.

2018-05-01

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

Thermophilic versus Mesophilic Anaerobic Digestion of Sewage Sludge: A Comparative Review

PubMed Central

Gebreeyessus, Getachew D.; Jenicek, Pavel

2016-01-01

During advanced biological wastewater treatment, a huge amount of sludge is produced as a by-product of the treatment process. Hence, reuse and recovery of resources and energy from the sludge is a big technological challenge. The processing of sludge produced by Wastewater Treatment Plants (WWTPs) is massive, which takes up a big part of the overall operational costs. In this regard, anaerobic digestion (AD) of sewage sludge continues to be an attractive option to produce biogas that could contribute to the wastewater management cost reduction and foster the sustainability of those WWTPs. At the same time, AD reduces sludge amounts and that again contributes to the reduction of the sludge disposal costs. However, sludge volume minimization remains, a challenge thus improvement of dewatering efficiency is an inevitable part of WWTP operation. As a result, AD parameters could have significant impact on sludge properties. One of the most important operational parameters influencing the AD process is temperature. Consequently, the thermophilic and the mesophilic modes of sludge AD are compared for their pros and cons by many researchers. However, most comparisons are more focused on biogas yield, process speed and stability. Regarding the biogas yield, thermophilic sludge AD is preferred over the mesophilic one because of its faster biochemical reaction rate. Equally important but not studied sufficiently until now was the influence of temperature on the digestate quality, which is expressed mainly by the sludge dewateringability, and the reject water quality (chemical oxygen demand, ammonia nitrogen, and pH). In the field of comparison of thermophilic and mesophilic digestion process, few and often inconclusive research, unfortunately, has been published so far. Hence, recommendations for optimized technologies have not yet been done. The review presented provides a comparison of existing sludge AD technologies and the gaps that need to be filled so as to optimize the connection between the two systems. In addition, many other relevant AD process parameters, including sludge rheology, which need to be addressed, are also reviewed and presented. PMID:28952577

On the parameters influencing air-water gas exchange

NASA Astrophysics Data System (ADS)

JäHne, Bernd; Münnich, Karl Otto; BöSinger, Rainer; Dutzi, Alfred; Huber, Werner; Libner, Peter

1987-02-01

Detailed gas exchange measurements from two circular and one linear wind/wave tunnels are presented. Heat, He, CH4, CO2, Kr, and Xe have been used as tracers. The experiments show the central importance of waves for the water-side transfer process. With the onset of waves the Schmidt number dependence of the transfer velocity k changes from k ∝ Sc-⅔ to k ∝ Sc-½indicating a change in the boundary conditions at the surface. Moreover, energy put into the wave field by wind is transferred to near-surface turbulence enhancing gas transfer. The data show that the mean square slope of the waves is the best parameter to characterize the free wavy surface with respect to water-side transfer processes.

Study of components and statistical reaction mechanism in simulation of nuclear process for optimized production of {sup 64}Cu and {sup 67}Ga medical radioisotopes using TALYS, EMPIRE and LISE++ nuclear reaction and evaporation codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nasrabadi, M. N., E-mail: mnnasrabadi@ast.ui.ac.ir; Sepiani, M.

2015-03-30

Production of medical radioisotopes is one of the most important tasks in the field of nuclear technology. These radioactive isotopes are mainly produced through variety nuclear process. In this research, excitation functions and nuclear reaction mechanisms are studied for simulation of production of these radioisotopes in the TALYS, EMPIRE and LISE++ reaction codes, then parameters and different models of nuclear level density as one of the most important components in statistical reaction models are adjusted for optimum production of desired radioactive yields.

Study of components and statistical reaction mechanism in simulation of nuclear process for optimized production of 64Cu and 67Ga medical radioisotopes using TALYS, EMPIRE and LISE++ nuclear reaction and evaporation codes

NASA Astrophysics Data System (ADS)

Nasrabadi, M. N.; Sepiani, M.

2015-03-01

Production of medical radioisotopes is one of the most important tasks in the field of nuclear technology. These radioactive isotopes are mainly produced through variety nuclear process. In this research, excitation functions and nuclear reaction mechanisms are studied for simulation of production of these radioisotopes in the TALYS, EMPIRE & LISE++ reaction codes, then parameters and different models of nuclear level density as one of the most important components in statistical reaction models are adjusted for optimum production of desired radioactive yields.

Flow Tube Studies of Gas Phase Chemical Processes of Atmospheric Importance

NASA Technical Reports Server (NTRS)

Molina, Mario J.

1998-01-01

The objective of this project is to conduct measurements of elementary reaction rate constants and photochemical parameters for processes of importance in the atmosphere. These measurements are being carried out under temperature and pressure conditions covering those applicable to the stratosphere and upper troposphere, using the chemical ionization mass spectrometry turbulent flow technique developed in our laboratory. The next section summarizes our research activities during the first year of the project, and the section that follows consists of the statement of work for the third year. Additional details concerning the projects listed in the statement of work were described in our original proposal.

Cyclic steaming in heavy oil diatomite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, M.; Beatty, F.D.

1995-12-31

Chevron currently uses cyclic steaming as a recovery method to produce economically its heavy oil diatomite resource in the Cymric field, San Joaquin Valley, California. A highly instrumented, cyclically steaming well from this field was simulated in this study to delineate important production mechanisms, to optimize operations, and to improve reservoir management. The model was constrained, as much as possible, by the available measured data. Results show that fluid flow from the well to the reservoir is primarily through the hydraulic fracture induced by the injected steam. Parameters with unique importance to modeling cyclic steaming in diatomites are: (1) inducedmore » fracture dimension (length and height), (2) matrix permeability, (3) oil/water capillary pressure, (4) grid size perpendicular to fracture face, and (5) producing bottomhole pressures. Additionally, parameters important for conventional steam injection processes, such as relative permeabilities and injected steam volume, quality, and rate, are important for diatomites also. Oil production rates and steam/oil ratios calculated by this model compare reasonably with field data.« less

CO2 injection into submarine, CH4-hydrate bearing sediments: Parameter studies towards the development of a hydrate conversion technology

NASA Astrophysics Data System (ADS)

Deusner, Christian; Bigalke, Nikolaus; Kossel, Elke; Haeckel, Matthias

2013-04-01

In the recent past, international research efforts towards exploitation of submarine and permafrost hydrate reservoirs have increased substantially. Until now, findings indicate that a combination of different technical means such as depressurization, thermal stimulation and chemical activation is the most promising approach for producing gas from natural hydrates. Moreover, emission neutral exploitation of CH4-hydrates could potentially be achieved in a combined process with CO2 injection and storage as CO2-hydrate. In the German gas hydrate initiative SUGAR, a combination of experimental and numerical studies is used to elucidate the process mechanisms and technical parameters on different scales. Experiments were carried out in the novel high-pressure flow-through system NESSI (Natural Environment Simulator for sub-Seafloor Interactions). Recent findings suggest that the injection of heated, supercritical CO2 is beneficial for both CH4 production and CO2 retention. Among the parameters tested so far are the CO2 injection regime (alternating vs. continuous injection) and the reservoir pressure / temperature conditions. Currently, the influence of CO2 injection temperature is investigated. It was shown that CH4 production is optimal at intermediate reservoir temperatures (8 ° C) compared to lower (2 ° C) and higher temperatures (10 ° C). The reservoir pressure, however, was of minor importance for the production efficiency. At 8 ° C, where CH4- and CO2-hydrates are thermodynamically stable, CO2-hydrate formation appears to be slow. Eventual clogging of fluid conduits due to CO2-rich hydrate formation force open new conduits, thereby tapping different regions inside the CH4-hydrate sample volume for CH4gas. In contrast, at 2 ° C immediate formation of CO2-hydrate results in rapid and irreversible obstruction of the entire pore space. At 10 ° C pure CO2-hydrates can no longer be formed. Consequently the injected CO2 flows through quickly and interaction with the reservoir is minimized. Our results clearly indicate that the formation of mixed CH4-CO2-hydrates is an important aspect in the conversion process. The experimental studies have shown that the injection of heated CO2 into the hydrate reservoir induces a variety of spatial and temporal processes which result in substantial bulk heterogeneity. Current numerical simulators are not able to predict these process dynamics and it is important to improve available transport-reaction models (e.g. to include the effect of bulk sediment permeability on the conversion dynamics). Our results confirm that experimental studies are important to better understand the mechanisms of hydrate dissociation and conversion at CO2-injection conditions as a basis towards the development of a suitable hydrate conversion technology. The application of non-invasive analytical methods such as Magnetic Resonance Imaging (MRI) and Raman microscopy are important tools, which were applied to resolve process dynamics on the pore scale. Additionally, the NESSI system is being modified to allow high-pressure flow-through experiments under triaxial loading to better simulate hydrate-sediment mechanics. This aspect is important for overall process development and evaluation of process safety issues.

Effect of process parameters on the density and porosity of laser melted AlSi10Mg/SiC metal matrix composite

NASA Astrophysics Data System (ADS)

Famodimu, Omotoyosi H.; Stanford, Mark; Oduoza, Chike F.; Zhang, Lijuan

2018-06-01

Laser melting of aluminium alloy—AlSi10Mg has increasingly been used to create specialised products in various industrial applications, however, research on utilising laser melting of aluminium matrix composites in replacing specialised parts have been slow on the uptake. This has been attributed to the complexity of the laser melting process, metal/ceramic feedstock for the process and the reaction of the feedstock material to the laser. Thus, an understanding of the process, material microstructure and mechanical properties is important for its adoption as a manufacturing route of aluminium metal matrix composites. The effects of several parameters of the laser melting process on the mechanical blended composite were thus investigated in this research. This included single track formations of the matrix alloy and the composite alloyed with 5% and 10% respectively for their reaction to laser melting and the fabrication of density blocks to investigate the relative density and porosity over different scan speeds. The results from these experiments were utilised in determining a process window in fabricating near-fully dense parts.

Parameterization guidelines and considerations for hydrologic models

USDA-ARS?s Scientific Manuscript database

Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and develo...

Biomedical implications of information processing in chemical systems: non-classical approach to photochemistry of coordination compounds.

PubMed

Szaciłowski, Konrad

2007-01-01

Analogies between photoactive nitric oxide generators and various electronic devices: logic gates and operational amplifiers are presented. These analogies have important biological consequences: application of control parameters allows for better targeting and control of nitric oxide drugs. The same methodology may be applied in the future for other therapeutic strategies and at the same time helps to understand natural regulatory and signaling processes in biological systems.

On-line Monitoring for Cutting Tool Wear Condition Based on the Parameters

NASA Astrophysics Data System (ADS)

Han, Fenghua; Xie, Feng

2017-07-01

In the process of cutting tools, it is very important to monitor the working state of the tools. On the basis of acceleration signal acquisition under the constant speed, time domain and frequency domain analysis of relevant indicators monitor the online of tool wear condition. The analysis results show that the method can effectively judge the tool wear condition in the process of machining. It has certain application value.

Modeling biological gradient formation: combining partial differential equations and Petri nets.

PubMed

Bertens, Laura M F; Kleijn, Jetty; Hille, Sander C; Heiner, Monika; Koutny, Maciej; Verbeek, Fons J

2016-01-01

Both Petri nets and differential equations are important modeling tools for biological processes. In this paper we demonstrate how these two modeling techniques can be combined to describe biological gradient formation. Parameters derived from partial differential equation describing the process of gradient formation are incorporated in an abstract Petri net model. The quantitative aspects of the resulting model are validated through a case study of gradient formation in the fruit fly.

The treatment of uncertainties in reactive pollution dispersion models at urban scales.

PubMed

Tomlin, A S; Ziehn, T; Goodman, P; Tate, J E; Dixon, N S

2016-07-18

The ability to predict NO2 concentrations ([NO2]) within urban street networks is important for the evaluation of strategies to reduce exposure to NO2. However, models aiming to make such predictions involve the coupling of several complex processes: traffic emissions under different levels of congestion; dispersion via turbulent mixing; chemical processes of relevance at the street-scale. Parameterisations of these processes are challenging to quantify with precision. Predictions are therefore subject to uncertainties which should be taken into account when using models within decision making. This paper presents an analysis of mean [NO2] predictions from such a complex modelling system applied to a street canyon within the city of York, UK including the treatment of model uncertainties and their causes. The model system consists of a micro-scale traffic simulation and emissions model, and a Reynolds averaged turbulent flow model coupled to a reactive Lagrangian particle dispersion model. The analysis focuses on the sensitivity of predicted in-street increments of [NO2] at different locations in the street to uncertainties in the model inputs. These include physical characteristics such as background wind direction, temperature and background ozone concentrations; traffic parameters such as overall demand and primary NO2 fraction; as well as model parameterisations such as roughness lengths, turbulent time- and length-scales and chemical reaction rate coefficients. Predicted [NO2] is shown to be relatively robust with respect to model parameterisations, although there are significant sensitivities to the activation energy for the reaction NO + O3 as well as the canyon wall roughness length. Under off-peak traffic conditions, demand is the key traffic parameter. Under peak conditions where the network saturates, road-side [NO2] is relatively insensitive to changes in demand and more sensitive to the primary NO2 fraction. The most important physical parameter was found to be the background wind direction. The study highlights the key parameters required for reliable [NO2] estimations suggesting that accurate reference measurements for wind direction should be a critical part of air quality assessments for in-street locations. It also highlights the importance of street scale chemical processes in forming road-side [NO2], particularly for regions of high NOx emissions such as close to traffic queues.

A Telemetry Browser Built with Java Components

NASA Astrophysics Data System (ADS)

Poupart, E.

In the context of CNES balloon scientific campaigns and telemetry survey field, a generic telemetry processing product, called TelemetryBrowser in the following, was developed reusing COTS, Java Components for most of them. Connection between those components relies on a software architecture based on parameter producers and parameter consumers. The first one transmit parameter values to the second one which has registered to it. All of those producers and consumers can be spread over the network thanks to Corba, and over every kind of workstation thanks to Java. This gives a very powerful mean to adapt to constraints like network bandwidth, or workstations processing or memory. It's also very useful to display and correlate at the same time information coming from multiple and various sources. An important point of this architecture is that the coupling between parameter producers and parameter consumers is reduced to the minimum and that transmission of information on the network is made asynchronously. So, if a parameter consumer goes down or runs slowly, there is no consequence on the other consumers, because producers don't wait for their consumers to finish their data processing before sending it to other consumers. An other interesting point is that parameter producers, also called TelemetryServers in the following are generated nearly automatically starting from a telemetry description using Flavori component. Keywords Java components, Corba, distributed application, OpenORBii, software reuse, COTS, Internet, Flavor. i Flavor (Formal Language for Audio-Visual Object Representation) is an object-oriented media representation language being developed at Columbia University. It is designed as an extension of Java and C++ and simplifies the development of applications that involve a significant media processing component (encoding, decoding, editing, manipulation, etc.) by providing bitstream representation semantics. (flavor.sourceforge.net) ii OpenORB provides a Java implementation of the OMG Corba 2.4.2 specification (openorb.sourceforge.net) 1/16

Sensitivities of Tropical Cyclones to Surface Friction and the Coriolis Parameter in a 2-D Cloud-Resolving Model

NASA Technical Reports Server (NTRS)

Chao, Winston C.; Chen, Baode; Tao, Wei-Kuo; Lau, William K. M. (Technical Monitor)

2002-01-01

The sensitivities to surface friction and the Coriolis parameter in tropical cyclogenesis are studied using an axisymmetric version of the Goddard cloud ensemble model. Our experiments demonstrate that tropical cyclogenesis can still occur without surface friction. However, the resulting tropical cyclone has very unrealistic structure. Surface friction plays an important role of giving the tropical cyclones their observed smaller size and diminished intensity. Sensitivity of the cyclogenesis process to surface friction. in terms of kinetic energy growth, has different signs in different phases of the tropical cyclone. Contrary to the notion of Ekman pumping efficiency, which implies a preference for the highest Coriolis parameter in the growth rate if all other parameters are unchanged, our experiments show no such preference.

[Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

PubMed

Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial heterogeneity under the three vegetation types. According to the temporal and spatial heterogeneity of the optimal values, the parameters of the BIOME-BGC model could be classified in order to adopt different parameter strategies in practical application. The conclusion could help to deeply understand the parameters and the optimal values of the ecological process models, and provide a way or reference for obtaining the reasonable values of parameters in models application.

Preparing and Publishing a Scientific Manuscript

PubMed Central

Jirge, Padma R.

2017-01-01

Publishing original research in a peer-reviewed and indexed journal is an important milestone for a scientist or a clinician. It is an important parameter to assess academic achievements. However, technical and language barriers may prevent many enthusiasts from ever publishing. This review highlights the important preparatory steps for creating a good manuscript and the most widely used IMRaD (Introduction, Materials and Methods, Results, and Discussion) method for writing a good manuscript. It also provides a brief overview of the submission and review process of a manuscript for publishing in a biomedical journal. PMID:28479749

Selection of Levels of Dressing Process Parameters by Using TOPSIS Technique for Surface Roughness of En-31 Work piece in CNC Cylindrical Grinding Machine

NASA Astrophysics Data System (ADS)

Patil, Sanjay S.; Bhalerao, Yogesh J.

2017-02-01

Grinding is metal cutting process used for mainly finishing the automobile components. The grinding wheel performance becomes dull by using it most of times. So it should be reshaping for consistent performance. It is necessary to remove dull grains of grinding wheel which is known as dressing process. The surface finish produced on the work piece is dependent on the dressing parameters in sub-sequent grinding operation. Multi-point diamond dresser has four important parameters such as the dressing cross feed rate, dressing depth of cut, width of the diamond dresser and drag angle of the dresser. The range of cross feed rate level is from 80-100 mm/min, depth of cut varies from 10 - 30 micron, width of diamond dresser is from 0.8 - 1.10mm and drag angle is from 40o - 500, The relative closeness to ideal levels of dressing parameters are found for surface finish produced on the En-31 work piece during sub-sequent grinding operation by using Technique of Order Preference by Similarity to Ideal Solution (TOPSIS).In the present work, closeness to ideal solution i.e. levels of dressing parameters are found for Computer Numerical Control (CNC) cylindrical angular grinding machine. After the TOPSIS technique, it is found that the value of Level I is 0.9738 which gives better surface finish on the En-31 work piece in sub-sequent grinding operation which helps the user to select the correct levels (combinations) of dressing parameters.

Study of Material Densification of In718 in the Higher Throughput Parameter Regime

NASA Technical Reports Server (NTRS)

Cordner, Samuel

2016-01-01

Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this project is to characterize how heat treatment affects density and porosity from a microscopic point of view. This is performs using higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. Density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, and hatch spacing) and material consolidation (assessed in terms of density and porosity). The study also considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the higher energy parameter regime. Metallurgical evaluation of specimens will also be presented. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

Ferronickel Preparation from Nickeliferous Laterite by Rotary Kiln-Electric Furnace Process

NASA Astrophysics Data System (ADS)

Li, Guanghui; Jia, Hao; Luo, Jun; Peng, Zhiwei; Zhang, Yuanbo; Jiang, Tao

Nickel is an important strategic metal, which is mainly used for stainless steel production. In the recent years, ferronickel has been used as a substitute for electrolytic nickel for alleviating the cost of stainless steel production. Rotary kiln-electric furnace (RKEF) smelting is currently the world-wide mainstreaming process for ferronickel production from nickeliferous laterite ore, in spite of the high power consumption. In this study, aiming to provide some meaningful guidance for ferronickel production of RKEF smelting, reductive roasting followed by smelting process was carried out. The conditions including reducing parameters (roasting temperature and time) and smelting parameters (coke dosage, CaO dosage, melting temperature and time) were ascertained. The metal recovery ratios, as well as Ni, Fe, S and P content of ferronickel were considered. The results showed that a ferronickel containing 10. 32 wt. % Ni was obtained from a laterite with 1. 85 wt. % Ni, the nickel recovery ratio was about 99%.

Generic Raman-based calibration models enabling real-time monitoring of cell culture bioreactors.

PubMed

Mehdizadeh, Hamidreza; Lauri, David; Karry, Krizia M; Moshgbar, Mojgan; Procopio-Melino, Renee; Drapeau, Denis

2015-01-01

Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration. © 2015 American Institute of Chemical Engineers.

Studies of Ionic Photoionization Using Relativistic Random Phase Approximation and Relativistic Multichannel Quantum Defect Theory

NASA Astrophysics Data System (ADS)

Haque, Ghousia Nasreen

The absorption of electromagnetic radiation by positive ions is one of the fundamental processes of nature which occurs in every intensely hot environment. Due to the difficulties in producing sufficient densities of ions in a laboratory, there are very few measurements of ionic photoabsorption parameters. On the theoretical side, some calculations have been made of a few major photoionization parameters, but generally speaking, most of the work done so far has employed rather simple single particle models and any theoretical work which has adequately taken into account intricate atomic many-body and relativistic effects is only scanty. In the present work, several complex aspects of atomic/ionic photoabsorption parameters have been studied. Non -resonant photoionization in neon and argon isonuclear as well as isoelectronic sequences has been studied using a very sophisticated technique, namely the relativistic random phase approximation (RRPA). This technique takes into account relativistic effects as well as an important class of major many-body effects on the same footing. The present calculations confirmed that gross features of photoionization parameters calculated using simpler models were not an artifact of the simple model. Also, the present RRPA calculations on K^+ ion and neutral Ar brought out the relative importance of various many-body effects such the inter-channel coupling. Inter-channel coupling between discrete bound state photoexcitation channels from an inner atomic/ionic level and photoionization continuum channels from an outer atomic/ionic level leads to the phenomena of autoionization resonances in the photoionization process. These resonances lead to very complex effects in the atomic/ionic photoabsorption spectra. These resonances have been calculated and studied in the present work in the neon and magnesium isoelectronic sequences using the relativistic multi-channel quantum defect theory (RMQDT) within the framework of the RRPA. The character of the autoionization resonances studied was determined in the present work and the effect of series perturbations in the Rydberg series due to interference between various multichannel processes was quantitatively determined. Furthermore, results of the present calculations also serve as important pointer to measure the relative strengths of radiative (fluorescence) decay modes and non -radiative (autoionization/auger) decay modes in an isoelectronic sequence.

Improved quantification of important beer quality parameters based on nonlinear calibration methods applied to FT-MIR spectra.

PubMed

Cernuda, Carlos; Lughofer, Edwin; Klein, Helmut; Forster, Clemens; Pawliczek, Marcin; Brandstetter, Markus

2017-01-01

During the production process of beer, it is of utmost importance to guarantee a high consistency of the beer quality. For instance, the bitterness is an essential quality parameter which has to be controlled within the specifications at the beginning of the production process in the unfermented beer (wort) as well as in final products such as beer and beer mix beverages. Nowadays, analytical techniques for quality control in beer production are mainly based on manual supervision, i.e., samples are taken from the process and analyzed in the laboratory. This typically requires significant lab technicians efforts for only a small fraction of samples to be analyzed, which leads to significant costs for beer breweries and companies. Fourier transform mid-infrared (FT-MIR) spectroscopy was used in combination with nonlinear multivariate calibration techniques to overcome (i) the time consuming off-line analyses in beer production and (ii) already known limitations of standard linear chemometric methods, like partial least squares (PLS), for important quality parameters Speers et al. (J I Brewing. 2003;109(3):229-235), Zhang et al. (J I Brewing. 2012;118(4):361-367) such as bitterness, citric acid, total acids, free amino nitrogen, final attenuation, or foam stability. The calibration models are established with enhanced nonlinear techniques based (i) on a new piece-wise linear version of PLS by employing fuzzy rules for local partitioning the latent variable space and (ii) on extensions of support vector regression variants (-PLSSVR and ν-PLSSVR), for overcoming high computation times in high-dimensional problems and time-intensive and inappropriate settings of the kernel parameters. Furthermore, we introduce a new model selection scheme based on bagged ensembles in order to improve robustness and thus predictive quality of the final models. The approaches are tested on real-world calibration data sets for wort and beer mix beverages, and successfully compared to linear methods, showing a clear out-performance in most cases and being able to meet the model quality requirements defined by the experts at the beer company. Figure Workflow for calibration of non-Linear model ensembles from FT-MIR spectra in beer production .

On-Ground Processing of Yaogan-24 Remote Sensing Satellite Attitude Data and Verification Using Geometric Field Calibration

PubMed Central

Wang, Mi; Fan, Chengcheng; Yang, Bo; Jin, Shuying; Pan, Jun

2016-01-01

Satellite attitude accuracy is an important factor affecting the geometric processing accuracy of high-resolution optical satellite imagery. To address the problem whereby the accuracy of the Yaogan-24 remote sensing satellite’s on-board attitude data processing is not high enough and thus cannot meet its image geometry processing requirements, we developed an approach involving on-ground attitude data processing and digital orthophoto (DOM) and the digital elevation model (DEM) verification of a geometric calibration field. The approach focuses on three modules: on-ground processing based on bidirectional filter, overall weighted smoothing and fitting, and evaluation in the geometric calibration field. Our experimental results demonstrate that the proposed on-ground processing method is both robust and feasible, which ensures the reliability of the observation data quality, convergence and stability of the parameter estimation model. In addition, both the Euler angle and quaternion could be used to build a mathematical fitting model, while the orthogonal polynomial fitting model is more suitable for modeling the attitude parameter. Furthermore, compared to the image geometric processing results based on on-board attitude data, the image uncontrolled and relative geometric positioning result accuracy can be increased by about 50%. PMID:27483287

Bayesian Analysis of Non-Gaussian Long-Range Dependent Processes

NASA Astrophysics Data System (ADS)

Graves, T.; Franzke, C.; Gramacy, R. B.; Watkins, N. W.

2012-12-01

Recent studies have strongly suggested that surface temperatures exhibit long-range dependence (LRD). The presence of LRD would hamper the identification of deterministic trends and the quantification of their significance. It is well established that LRD processes exhibit stochastic trends over rather long periods of time. Thus, accurate methods for discriminating between physical processes that possess long memory and those that do not are an important adjunct to climate modeling. We have used Markov Chain Monte Carlo algorithms to perform a Bayesian analysis of Auto-Regressive Fractionally-Integrated Moving-Average (ARFIMA) processes, which are capable of modeling LRD. Our principal aim is to obtain inference about the long memory parameter, d,with secondary interest in the scale and location parameters. We have developed a reversible-jump method enabling us to integrate over different model forms for the short memory component. We initially assume Gaussianity, and have tested the method on both synthetic and physical time series such as the Central England Temperature. Many physical processes, for example the Faraday time series from Antarctica, are highly non-Gaussian. We have therefore extended this work by weakening the Gaussianity assumption. Specifically, we assume a symmetric α -stable distribution for the innovations. Such processes provide good, flexible, initial models for non-Gaussian processes with long memory. We will present a study of the dependence of the posterior variance σ d of the memory parameter d on the length of the time series considered. This will be compared with equivalent error diagnostics for other measures of d.

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Models for selecting GMA Welding Parameters for Improving Mechanical Properties of Weld Joints

NASA Astrophysics Data System (ADS)

Srinivasa Rao, P.; Ramachandran, Pragash; Jebaraj, S.

2016-02-01

During the process of Gas Metal Arc (GMAW) welding, the weld joints mechanical properties are influenced by the welding parameters such as welding current and arc voltage. These parameters directly will influence the quality of the weld in terms of mechanical properties. Even small variation in any of the cited parameters may have an important effect on depth of penetration and on joint strength. In this study, S45C Constructional Steel is taken as the base metal to be tested using the parameters wire feed rate, voltage and type of shielding gas. Physical properties considered in the present study are tensile strength and hardness. The testing of weld specimen is carried out as per ASTM Standards. Mathematical models to predict the tensile strength and depth of penetration of weld joint have been developed by regression analysis using the experimental results.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data.

PubMed

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S; Windus, Theresa L; Dick-Perez, Marilu

2017-03-27

A newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit. ParFit is in an open source program available for free on GitHub ( https://github.com/fzahari/ParFit ).

Combined micromechanical and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, C. C.

1991-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

A time to search: finding the meaning of variable activation energy.

PubMed

Vyazovkin, Sergey

2016-07-28

This review deals with the phenomenon of variable activation energy frequently observed when studying the kinetics in the liquid or solid phase. This phenomenon commonly manifests itself through nonlinear Arrhenius plots or dependencies of the activation energy on conversion computed by isoconversional methods. Variable activation energy signifies a multi-step process and has a meaning of a collective parameter linked to the activation energies of individual steps. It is demonstrated that by using appropriate models of the processes, the link can be established in algebraic form. This allows one to analyze experimentally observed dependencies of the activation energy in a quantitative fashion and, as a result, to obtain activation energies of individual steps, to evaluate and predict other important parameters of the process, and generally to gain deeper kinetic and mechanistic insights. This review provides multiple examples of such analysis as applied to the processes of crosslinking polymerization, crystallization and melting of polymers, gelation, and solid-solid morphological and glass transitions. The use of appropriate computational techniques is discussed as well.

Concurrent micromechanical tailoring and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, Christos C.

1990-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

Thermodynamic Analysis for the Refining Ability of Salt Flux for Aluminum Recycling

PubMed Central

Hiraki, Takehito; Miki, Takahiro; Nakajima, Kenichi; Matsubae, Kazuyo; Nakamura, Shinichiro; Nagasaka, Tetsuya

2014-01-01

The removability of impurities during the aluminum remelting process by oxidation was previously investigated by our research group. In the present work, alternative impurity removal with chlorination has been evaluated by thermodynamic analysis. For 43 different elements, equilibrium distribution ratios among metal, chloride flux and oxide slag phases in the aluminum remelting process were calculated by assuming the binary systems of aluminum and an impurity element. It was found that the removability of impurities isn’t significantly affected by process parameters such as chloride partial pressure, temperature and flux composition. It was shown that Ho, Dy, Li, La, Mg, Gd, Ce, Yb, Ca and Sr can be potentially eliminated into flux by chlorination from the remelted aluminum. Chlorination and oxidation are not effective to remove other impurities from the melting aluminum, due to the limited parameters which can be controlled during the remelting process. It follows that a proper management of aluminum scrap such as sorting based on the composition of the products is important for sustainable aluminum recycling. PMID:28788144

Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system

USGS Publications Warehouse

Ely, D. Matthew

2006-01-01

Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow routing parameter. Although the primary objective of this study was to identify, by geographic region, the importance of the parameter value to the simulation of ground-water recharge, the secondary objectives proved valuable for future modeling efforts. The value of a rigorous sensitivity analysis can (1) make the calibration process more efficient, (2) guide additional data collection, (3) identify model limitations, and (4) explain simulated results.

Assessment of parameter uncertainty in hydrological model using a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis method

NASA Astrophysics Data System (ADS)

Zhang, Junlong; Li, Yongping; Huang, Guohe; Chen, Xi; Bao, Anming

2016-07-01

Without a realistic assessment of parameter uncertainty, decision makers may encounter difficulties in accurately describing hydrologic processes and assessing relationships between model parameters and watershed characteristics. In this study, a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis (MCMC-MFA) method is developed, which can not only generate samples of parameters from a well constructed Markov chain and assess parameter uncertainties with straightforward Bayesian inference, but also investigate the individual and interactive effects of multiple parameters on model output through measuring the specific variations of hydrological responses. A case study is conducted for addressing parameter uncertainties in the Kaidu watershed of northwest China. Effects of multiple parameters and their interactions are quantitatively investigated using the MCMC-MFA with a three-level factorial experiment (totally 81 runs). A variance-based sensitivity analysis method is used to validate the results of parameters' effects. Results disclose that (i) soil conservation service runoff curve number for moisture condition II (CN2) and fraction of snow volume corresponding to 50% snow cover (SNO50COV) are the most significant factors to hydrological responses, implying that infiltration-excess overland flow and snow water equivalent represent important water input to the hydrological system of the Kaidu watershed; (ii) saturate hydraulic conductivity (SOL_K) and soil evaporation compensation factor (ESCO) have obvious effects on hydrological responses; this implies that the processes of percolation and evaporation would impact hydrological process in this watershed; (iii) the interactions of ESCO and SNO50COV as well as CN2 and SNO50COV have an obvious effect, implying that snow cover can impact the generation of runoff on land surface and the extraction of soil evaporative demand in lower soil layers. These findings can help enhance the hydrological model's capability for simulating/predicting water resources.

Energy Efficient and QoS sensitive Routing Protocol for Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Saeed Tanoli, Tariq; Khalid Khan, Muhammad

2013-12-01

Efficient routing is an important part of wireless ad hoc networks. Since in ad hoc networks we have limited resources, there are many limitations like bandwidth, battery consumption, and processing cycle etc. Reliability is also necessary since there is no allowance for invalid or incomplete information (and expired data is useless). There are various protocols that perform routing by considering one parameter but ignoring other parameters. In this paper we present a protocol that finds route on the basis of bandwidth, energy and mobility of the nodes participating in the communication.

Investigating Musical Disorders with Diffusion Tensor Imaging: a Comparison of Imaging Parameters

PubMed Central

Loui, Psyche; Schlaug, Gottfried

2009-01-01

The Arcuate Fasciculus (AF) is a bundle of white matter traditionally thought to be responsible for language function. However, its role in music is not known. Here we investigate the connectivity of the AF using Diffusion Tensor Imaging (DTI) and show that musically tone-deaf individuals, who show impairments in pitch discrimination, have reduced connectivity in the AF relative to musically normal-functioning control subjects. Results were robust to variations in imaging parameters and emphasize the importance of brain connectivity in para-linguistic processes such as music. PMID:19673766

Design and performance study of an orthopaedic surgery robotized module for automatic bone drilling.

PubMed

Boiadjiev, George; Kastelov, Rumen; Boiadjiev, Tony; Kotev, Vladimir; Delchev, Kamen; Zagurski, Kazimir; Vitkov, Vladimir

2013-12-01

Many orthopaedic operations involve drilling and tapping before the insertion of screws into a bone. This drilling is usually performed manually, thus introducing many problems. These include attaining a specific drilling accuracy, preventing blood vessels from breaking, and minimizing drill oscillations that would widen the hole. Bone overheating is the most important problem. To avoid such problems and reduce the subjective factor, automated drilling is recommended. Because numerous parameters influence the drilling process, this study examined some experimental methods. These concerned the experimental identification of technical drilling parameters, including the bone resistance force and temperature in the drilling process. During the drilling process, the following parameters were monitored: time, linear velocity, angular velocity, resistance force, penetration depth, and temperature. Specific drilling effects were revealed during the experiments. The accuracy was improved at the starting point of the drilling, and the error for the entire process was less than 0.2 mm. The temperature deviations were kept within tolerable limits. The results of various experiments with different drilling velocities, drill bit diameters, and penetration depths are presented in tables, as well as the curves of the resistance force and temperature with respect to time. Real-time digital indications of the progress of the drilling process are shown. Automatic bone drilling could entirely solve the problems that usually arise during manual drilling. An experimental setup was designed to identify bone drilling parameters such as the resistance force arising from variable bone density, appropriate mechanical drilling torque, linear speed of the drill, and electromechanical characteristics of the motors, drives, and corresponding controllers. Automatic drilling guarantees greater safety for the patient. Moreover, the robot presented is user-friendly because it is simple to set robot tasks, and process data are collected in real time. Copyright © 2013 John Wiley & Sons, Ltd.

Combat Ration Advanced Manufacturing Technology Demonstration (CRAMTD). ’Generic Inspection-Statistical Process Control System for a Combat Ration Manufacturing Facility’. Short Term Project (STP) Number 3.

DTIC Science & Technology

1996-01-01

failure as due to an adhesive layer between the foil and inner polypropylene layers. "* Under subcontract, NFPA provided HACCP draft manuals for the...parameters of the production process and to ensure that they are within their target values. In addition, a HACCP program was used to assure product...played an important part in implementing Hazard Analysis Critical Control Points ( HACCP ) as part of the Process and Quality Control manual. The National

β-decay studies of r-process nuclei at NSCL

NASA Astrophysics Data System (ADS)

Pereira, J.; Aprahamian, A.; Arndt, O.; Becerril, A.; Elliot, T.; Estrade, A.; Galaviz, D.; Hennrich, S.; Hosmer, P.; Schnorrenberger, L.; Kessler, R.; Kratz, K.-L.; Lorusso, G.; Mantica, P. F.; Matos, M.; Montes, F.; Pfeiffer, B.; Quinn, M.; Santi, P.; Schatz, H.; Schertz, F.; Smith, E.; Tomlin, B. E.; Walters, W. B.; Wöhr, A.

2008-06-01

Observed neutron-capture elemental abundances in metal-poor stars, along with ongoing analysis of the extremely metal-poor Eu-enriched sub-class provide new guidance for astrophysical models aimed at finding the r-process sites. The present paper emphasizes the importance of nuclear physics parameters entering in these models, particularly β-decay properties of neutron-rich nuclei. In this context, several r-process motivated β-decay experiments performed at the National Superconducting Cyclotron Laboratory (NSCL) are presented, including a summary of results and impact on model calculations.

Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population.

PubMed

Jin, Hui; Wen, Weie; Liu, Jindong; Zhai, Shengnan; Zhang, Yan; Yan, Jun; Liu, Zhiyong; Xia, Xianchun; He, Zhonghu

2016-01-01

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat.

Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population

PubMed Central

Jin, Hui; Wen, Weie; Liu, Jindong; Zhai, Shengnan; Zhang, Yan; Yan, Jun; Liu, Zhiyong; Xia, Xianchun; He, Zhonghu

2016-01-01

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat. PMID:27486464

An empirical-statistical model for laser cladding of Ti-6Al-4V powder on Ti-6Al-4V substrate

NASA Astrophysics Data System (ADS)

Nabhani, Mohammad; Razavi, Reza Shoja; Barekat, Masoud

2018-03-01

In this article, Ti-6Al-4V powder alloy was directly deposited on Ti-6Al-4V substrate using laser cladding process. In this process, some key parameters such as laser power (P), laser scanning rate (V) and powder feeding rate (F) play important roles. Using linear regression analysis, this paper develops the empirical-statistical relation between these key parameters and geometrical characteristics of single clad tracks (i.e. clad height, clad width, penetration depth, wetting angle, and dilution) as a combined parameter (PαVβFγ). The results indicated that the clad width linearly depended on PV-1/3 and powder feeding rate had no effect on it. The dilution controlled by a combined parameter as VF-1/2 and laser power was a dispensable factor. However, laser power was the dominant factor for the clad height, penetration depth, and wetting angle so that they were proportional to PV-1F1/4, PVF-1/8, and P3/4V-1F-1/4, respectively. Based on the results of correlation coefficient (R > 0.9) and analysis of residuals, it was confirmed that these empirical-statistical relations were in good agreement with the measured values of single clad tracks. Finally, these relations led to the design of a processing map that can predict the geometrical characteristics of the single clad tracks based on the key parameters.

Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

NASA Technical Reports Server (NTRS)

Schumann, Johann Martin Philip; Cate, Karen; Lee, Alan G.

2010-01-01

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

Microstructure based simulations for prediction of flow curves and selection of process parameters for inter-critical annealing in DP steel

NASA Astrophysics Data System (ADS)

Deepu, M. J.; Farivar, H.; Prahl, U.; Phanikumar, G.

2017-04-01

Dual phase steels are versatile advanced high strength steels that are being used for sheet metal applications in automotive industry. It also has the potential for application in bulk components like gear. The inter-critical annealing in dual phase steels is one of the crucial steps that determine the mechanical properties of the material. Selection of the process parameters for inter-critical annealing, in particular, the inter-critical annealing temperature and time is important as it plays a major role in determining the volume fractions of ferrite and martensite, which in turn determines the mechanical properties. Selection of these process parameters to obtain a particular required mechanical property requires large number of experimental trials. Simulation of microstructure evolution and virtual compression/tensile testing can help in reducing the number of such experimental trials. In the present work, phase field modeling implemented in the commercial software Micress® is used to predict the microstructure evolution during inter-critical annealing. Virtual compression tests are performed on the simulated microstructure using finite element method implemented in the commercial software, to obtain the effective flow curve of the macroscopic material. The flow curves obtained by simulation are experimentally validated with physical simulation in Gleeble® and compared with that obtained using linear rule of mixture. The methodology could be used in determining the inter-critical annealing process parameters required for achieving a particular flow curve.

Design of experiments reveals critical parameters for pilot-scale freeze-and-thaw processing of L-lactic dehydrogenase.

PubMed

Roessl, Ulrich; Humi, Sebastian; Leitgeb, Stefan; Nidetzky, Bernd

2015-09-01

Freezing constitutes an important unit operation of biotechnological protein production. Effects of freeze-and-thaw (F/T) process parameters on stability and other quality attributes of the protein product are usually not well understood. Here a design of experiments (DoE) approach was used to characterize the F/T behavior of L-lactic dehydrogenase (LDH) in a 700-mL pilot-scale freeze container equipped with internal temperature and pH probes. In 24-hour experiments, target temperature between -10 and -38°C most strongly affected LDH stability whereby enzyme activity was retained best at the highest temperature of -10°C. Cooling profile and liquid fill volume also had significant effects on LDH stability and affected the protein aggregation significantly. Parameters of the thawing phase had a comparably small effect on LDH stability. Experiments in which the standard sodium phosphate buffer was exchanged by Tris-HCl and the non-ionic surfactant Tween 80 was added to the protein solution showed that pH shift during freezing and protein surface exposure were the main factors responsible for LDH instability at the lower freeze temperatures. Collectively, evidence is presented that supports the use of DoE-based systematic analysis at pilot scale in the identification of F/T process parameters critical for protein stability and in the development of suitable process control strategies. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs. Biotechnol. Bioeng. 2017;114: 589-599. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Results from a first production of enhanced Silicon Sensor Test Structures produced by ITE Warsaw

NASA Astrophysics Data System (ADS)

Bergauer, T.; Dragicevic, M.; Frey, M.; Grabiec, P.; Grodner, M.; Hänsel, S.; Hartmann, F.; Hoffmann, K.-H.; Hrubec, J.; Krammer, M.; Kucharski, K.; Macchiolo, A.; Marczewski, J.

2009-01-01

Monitoring the manufacturing process of silicon sensors is essential to ensure stable quality of the produced detectors. During the CMS silicon sensor production we were utilising small Test Structures (TS) incorporated on the cut-away of the wafers to measure certain process-relevant parameters. Experience from the CMS production and quality assurance led to enhancements of these TS. Another important application of TS is the commissioning of new vendors. The measurements provide us with a good understanding of the capabilities of a vendor's process. A first batch of the new TS was produced at the Institute of Electron Technology in Warsaw Poland. We will first review the improvements to the original CMS test structures and then discuss a selection of important measurements performed on this first batch.

Rational Design of Molecular Gelator - Solvent Systems Guided by Solubility Parameters

NASA Astrophysics Data System (ADS)

Lan, Yaqi

Self-assembled architectures, such as molecular gels, have attracted wide interest among chemists, physicists and engineers during the past decade. However, the mechanism behind self-assembly remains largely unknown and no capability exists to predict a priori whether a small molecule will gelate a specific solvent or not. The process of self-assembly, in molecular gels, is intricate and must balance parameters influencing solubility and those contrasting forces that govern epitaxial growth into axially symmetric elongated aggregates. Although the gelator-gelator interactions are of paramount importance in understanding gelation, the solvent-gelator specific (i.e., H-bonding) and nonspecific (dipole-dipole, dipole-induced and instantaneous dipole induced forces) intermolecular interactions are equally important. Solvent properties mediate the self-assembly of molecular gelators into their self-assembled fibrillar networks. Herein, solubility parameters of solvents, ranging from partition coefficients (logP), to Henry's law constants (HLC), to solvatochromic ET(30) parameters, to Kamlet-Taft parameters (beta, alpha and pi), to Hansen solubility parameters (deltap, deltad, deltah), etc., are correlated with the gelation ability of numerous classes of molecular gelators. Advanced solvent clustering techniques have led to the development of a priori tools that can identify the solvents that will be gelled and not gelled by molecular gelators. These tools will greatly aid in the development of novel gelators without solely relying on serendipitous discoveries.

Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

PubMed Central

Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

2012-01-01

Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the six FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225

Automated live cell screening system based on a 24-well-microplate with integrated micro fluidics.

PubMed

Lob, V; Geisler, T; Brischwein, M; Uhl, R; Wolf, B

2007-11-01

In research, pharmacologic drug-screening and medical diagnostics, the trend towards the utilization of functional assays using living cells is persisting. Research groups working with living cells are confronted with the problem, that common endpoint measurement methods are not able to map dynamic changes. With consideration of time as a further dimension, the dynamic and networked molecular processes of cells in culture can be monitored. These processes can be investigated by measuring several extracellular parameters. This paper describes a high-content system that provides real-time monitoring data of cell parameters (metabolic and morphological alterations), e.g., upon treatment with drug compounds. Accessible are acidification rates, the oxygen consumption and changes in adhesion forces within 24 cell cultures in parallel. Addressing the rising interest in biomedical and pharmacological high-content screening assays, a concept has been developed, which integrates multi-parametric sensor readout, automated imaging and probe handling into a single embedded platform. A life-maintenance system keeps important environmental parameters (gas, humidity, sterility, temperature) constant.

Effects of morphology parameters on anti-icing performance in superhydrophobic surfaces

NASA Astrophysics Data System (ADS)

Nguyen, Thanh-Binh; Park, Seungchul; Lim, Hyuneui

2018-03-01

In this paper, we report the contributions of actual ice-substrate contact area and nanopillar height to passive anti-icing performance in terms of adhesion force and freezing time. Well-textured nanopillars with various parameters were fabricated via colloidal lithography and a dry etching process. The nanostructured quartz surface was coated with low-energy material to confer water-repellent properties. These superhydrophobic surfaces were investigated to determine the parameters essential for reducing adhesion strength and delaying freezing time. A well-textured surface with nanopillars of very small top diameter, regardless of height, could reduce adhesion force and delay freezing time in a subsequent de-icing process. Small top diameters of nanopillars also ensured the metastable Cassie-Baxter state based on energy barrier calculations. The results demonstrated the important role of areal fraction in anti-icing efficiency, and the negligible contribution of texture height. This insight into icing phenomena should lead to design of improved ice-phobic surfaces in the future.

Panaceas, uncertainty, and the robust control framework in sustainability science

PubMed Central

Anderies, John M.; Rodriguez, Armando A.; Janssen, Marco A.; Cifdaloz, Oguzhan

2007-01-01

A critical challenge faced by sustainability science is to develop strategies to cope with highly uncertain social and ecological dynamics. This article explores the use of the robust control framework toward this end. After briefly outlining the robust control framework, we apply it to the traditional Gordon–Schaefer fishery model to explore fundamental performance–robustness and robustness–vulnerability trade-offs in natural resource management. We find that the classic optimal control policy can be very sensitive to parametric uncertainty. By exploring a large class of alternative strategies, we show that there are no panaceas: even mild robustness properties are difficult to achieve, and increasing robustness to some parameters (e.g., biological parameters) results in decreased robustness with respect to others (e.g., economic parameters). On the basis of this example, we extract some broader themes for better management of resources under uncertainty and for sustainability science in general. Specifically, we focus attention on the importance of a continual learning process and the use of robust control to inform this process. PMID:17881574

Bayesian parameter estimation for stochastic models of biological cell migration

NASA Astrophysics Data System (ADS)

Dieterich, Peter; Preuss, Roland

2013-08-01

Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.

Influence of sputtering deposition parameters on electrical and optical properties of aluminium-doped zinc oxide thin films for photovoltaic applications

NASA Astrophysics Data System (ADS)

Krawczak, Ewelina; Agata, Zdyb; Gulkowski, Slawomir; Fave, Alain; Fourmond, Erwann

2017-11-01

Transparent Conductive Oxides (TCOs) characterized by high visible transmittance and low electrical resistivity play an important role in photovoltaic technology. Aluminum doped zinc oxide (AZO) is one of the TCOs that can find its application in thin film solar cells (CIGS or CdTe PV technology) as well as in other microelectronic applications. In this paper some optical and electrical properties of ZnO:Al thin films deposited by RF magnetron sputtering method have been investigated. AZO layers have been deposited on the soda lime glass substrates with use of variable technological parameters such as pressure in the deposition chamber, power applied and temperature during the process. The composition of AZO films has been investigated by EDS method. Thickness and refraction index of the deposited layers in dependence on certain technological parameters of sputtering process have been determined by spectroscopic ellipsometry. The measurements of transmittance and sheet resistance were also performed.

Adjustment of Part Properties for an Elastomeric Laser Sintering Material

NASA Astrophysics Data System (ADS)

Wegner, A.; Ünlü, T.

2018-03-01

Laser sintering of polymers is gaining more and more importance within the field of small series productions. Polyamide 12 is predominantly used, although a variety of other materials are also available for the laser sintering process. For example, elastomeric, rubberlike materials offer very different part property profiles. Those make the production of flexible parts like, e.g., sealings, flexible tubes or shoe soles possible because they offer high part ductility and low hardness. At the chair for manufacturing technology, a new elastomeric laser sintering material has been developed and then commercialized by a spin-off from university. The aim of the presented study was the analysis of the new material's properties. Proof was found that Shore hardness can be modified by varying the parameter settings. Therefore, the correlation between process parameters, energy input, Shore hardness and other part properties like mechanical properties were analyzed. Based on these results, suitable parameter settings were established which lead to the possibility of producing parts with different Shore hardnesses.

Wave data processing toolbox manual

USGS Publications Warehouse

Sullivan, Charlene M.; Warner, John C.; Martini, Marinna A.; Lightsom, Frances S.; Voulgaris, George; Work, Paul

2006-01-01

Researchers routinely deploy oceanographic equipment in estuaries, coastal nearshore environments, and shelf settings. These deployments usually include tripod-mounted instruments to measure a suite of physical parameters such as currents, waves, and pressure. Instruments such as the RD Instruments Acoustic Doppler Current Profiler (ADCP(tm)), the Sontek Argonaut, and the Nortek Aquadopp(tm) Profiler (AP) can measure these parameters. The data from these instruments must be processed using proprietary software unique to each instrument to convert measurements to real physical values. These processed files are then available for dissemination and scientific evaluation. For example, the proprietary processing program used to process data from the RD Instruments ADCP for wave information is called WavesMon. Depending on the length of the deployment, WavesMon will typically produce thousands of processed data files. These files are difficult to archive and further analysis of the data becomes cumbersome. More imperative is that these files alone do not include sufficient information pertinent to that deployment (metadata), which could hinder future scientific interpretation. This open-file report describes a toolbox developed to compile, archive, and disseminate the processed wave measurement data from an RD Instruments ADCP, a Sontek Argonaut, or a Nortek AP. This toolbox will be referred to as the Wave Data Processing Toolbox. The Wave Data Processing Toolbox congregates the processed files output from the proprietary software into two NetCDF files: one file contains the statistics of the burst data and the other file contains the raw burst data (additional details described below). One important advantage of this toolbox is that it converts the data into NetCDF format. Data in NetCDF format is easy to disseminate, is portable to any computer platform, and is viewable with public-domain freely-available software. Another important advantage is that a metadata structure is embedded with the data to document pertinent information regarding the deployment and the parameters used to process the data. Using this format ensures that the relevant information about how the data was collected and converted to physical units is maintained with the actual data. EPIC-standard variable names have been utilized where appropriate. These standards, developed by the NOAA Pacific Marine Environmental Laboratory (PMEL) (http://www.pmel.noaa.gov/epic/), provide a universal vernacular allowing researchers to share data without translation.

Radiotracer Technology in Mixing Processes for Industrial Applications

PubMed Central

Othman, N.; Kamarudin, S. K.

2014-01-01

Many problems associated with the mixing process remain unsolved and result in poor mixing performance. The residence time distribution (RTD) and the mixing time are the most important parameters that determine the homogenisation that is achieved in the mixing vessel and are discussed in detail in this paper. In addition, this paper reviews the current problems associated with conventional tracers, mathematical models, and computational fluid dynamics simulations involved in radiotracer experiments and hybrid of radiotracer. PMID:24616642

Application of process analytical technology for monitoring freeze-drying of an amorphous protein formulation: use of complementary tools for real-time product temperature measurements and endpoint detection.

PubMed

Schneid, Stefan C; Johnson, Robert E; Lewis, Lavinia M; Stärtzel, Peter; Gieseler, Henning

2015-05-01

Process analytical technology (PAT) and quality by design have gained importance in all areas of pharmaceutical development and manufacturing. One important method for monitoring of critical product attributes and process optimization in laboratory scale freeze-drying is manometric temperature measurement (MTM). A drawback of this innovative technology is that problems are encountered when processing high-concentrated amorphous materials, particularly protein formulations. In this study, a model solution of bovine serum albumin and sucrose was lyophilized at both conservative and aggressive primary drying conditions. Different temperature sensors were employed to monitor product temperatures. The residual moisture content at primary drying endpoints as indicated by temperature sensors and batch PAT methods was quantified from extracted sample vials. The data from temperature probes were then used to recalculate critical product parameters, and the results were compared with MTM data. The drying endpoints indicated by the temperature sensors were not suitable for endpoint indication, in contrast to the batch methods endpoints. The accuracy of MTM Pice data was found to be influenced by water reabsorption. Recalculation of Rp and Pice values based on data from temperature sensors and weighed vials was possible. Overall, extensive information about critical product parameters could be obtained using data from complementary PAT tools. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Quantitative Förster resonance energy transfer analysis for kinetic determinations of SUMO-specific protease.

PubMed

Liu, Yan; Song, Yang; Madahar, Vipul; Liao, Jiayu

2012-03-01

Förster resonance energy transfer (FRET) technology has been widely used in biological and biomedical research, and it is a very powerful tool for elucidating protein interactions in either dynamic or steady state. SUMOylation (the process of SUMO [small ubiquitin-like modifier] conjugation to substrates) is an important posttranslational protein modification with critical roles in multiple biological processes. Conjugating SUMO to substrates requires an enzymatic cascade. Sentrin/SUMO-specific proteases (SENPs) act as an endopeptidase to process the pre-SUMO or as an isopeptidase to deconjugate SUMO from its substrate. To fully understand the roles of SENPs in the SUMOylation cycle, it is critical to understand their kinetics. Here, we report a novel development of a quantitative FRET-based protease assay for SENP1 kinetic parameter determination. The assay is based on the quantitative analysis of the FRET signal from the total fluorescent signal at acceptor emission wavelength, which consists of three components: donor (CyPet-SUMO1) emission, acceptor (YPet) emission, and FRET signal during the digestion process. Subsequently, we developed novel theoretical and experimental procedures to determine the kinetic parameters, k(cat), K(M), and catalytic efficiency (k(cat)/K(M)) of catalytic domain SENP1 toward pre-SUMO1. Importantly, the general principles of this quantitative FRET-based protease kinetic determination can be applied to other proteases. Copyright © 2011 Elsevier Inc. All rights reserved.

Method for laser spot welding monitoring

NASA Astrophysics Data System (ADS)

Manassero, Giorgio

1994-09-01

As more powerful solid state laser sources appear on the market, new applications become technically possible and important from the economical point of view. For every process a preliminary optimization phase is necessary. The main parameters, used for a welding application by a high power Nd-YAG laser, are: pulse energy, pulse width, repetition rate and process duration or speed. In this paper an experimental methodology, for the development of an electrooptical laser spot welding monitoring system, is presented. The electromagnetic emission from the molten pool was observed and measured with appropriate sensors. The statistical method `Parameter Design' was used to obtain an accurate analysis of the process parameter that influence process results. A laser station with a solid state laser coupled to an optical fiber (1 mm in diameter) was utilized for the welding tests. The main material used for the experimental plan was zinc coated steel sheet 0.8 mm thick. This material and the related spot welding technique are extensively used in the automotive industry, therefore, the introduction of laser technology in production line will improve the quality of the final product. A correlation, between sensor signals and `through or not through' welds, was assessed. The investigation has furthermore shown the necessity, for the modern laser production systems, to use multisensor heads for process monitoring or control with more advanced signal elaboration procedures.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Parameter Sensitivity and Laboratory Benchmarking of a Biogeochemical Process Model for Enhanced Anaerobic Dechlorination

NASA Astrophysics Data System (ADS)

Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.

2008-12-01

A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems, particularly at the laboratory scale.

An Interoperability Consideration in Selecting Domain Parameters for Elliptic Curve Cryptography

NASA Technical Reports Server (NTRS)

Ivancic, Will (Technical Monitor); Eddy, Wesley M.

2005-01-01

Elliptic curve cryptography (ECC) will be an important technology for electronic privacy and authentication in the near future. There are many published specifications for elliptic curve cryptosystems, most of which contain detailed descriptions of the process for the selection of domain parameters. Selecting strong domain parameters ensures that the cryptosystem is robust to attacks. Due to a limitation in several published algorithms for doubling points on elliptic curves, some ECC implementations may produce incorrect, inconsistent, and incompatible results if domain parameters are not carefully chosen under a criterion that we describe. Few documents specify the addition or doubling of points in such a manner as to avoid this problematic situation. The safety criterion we present is not listed in any ECC specification we are aware of, although several other guidelines for domain selection are discussed in the literature. We provide a simple example of how a set of domain parameters not meeting this criterion can produce catastrophic results, and outline a simple means of testing curve parameters for interoperable safety over doubling.

Using Bayesian regression to test hypotheses about relationships between parameters and covariates in cognitive models.

PubMed

Boehm, Udo; Steingroever, Helen; Wagenmakers, Eric-Jan

2018-06-01

An important tool in the advancement of cognitive science are quantitative models that represent different cognitive variables in terms of model parameters. To evaluate such models, their parameters are typically tested for relationships with behavioral and physiological variables that are thought to reflect specific cognitive processes. However, many models do not come equipped with the statistical framework needed to relate model parameters to covariates. Instead, researchers often revert to classifying participants into groups depending on their values on the covariates, and subsequently comparing the estimated model parameters between these groups. Here we develop a comprehensive solution to the covariate problem in the form of a Bayesian regression framework. Our framework can be easily added to existing cognitive models and allows researchers to quantify the evidential support for relationships between covariates and model parameters using Bayes factors. Moreover, we present a simulation study that demonstrates the superiority of the Bayesian regression framework to the conventional classification-based approach.

Kinetics, isothermal and thermodynamics studies of electrocoagulation removal of basic dye rhodamine B from aqueous solution using steel electrodes

NASA Astrophysics Data System (ADS)

Adeogun, Abideen Idowu; Balakrishnan, Ramesh Babu

2017-07-01

Electrocoagulation was used for the removal of basic dye rhodamine B from aqueous solution, and the process was carried out in a batch electrochemical cell with steel electrodes in monopolar connection. The effects of some important parameters such as current density, pH, temperature and initial dye concentration, on the process, were investigated. Equilibrium was attained after 10 min at 30 °C. Pseudo-first-order, pseudo-second-order, Elovich and Avrami kinetic models were used to test the experimental data in order to elucidate the kinetic adsorption process; pseudo-first-order and Avrami models best fitted the data. Experimental data were analysed using six model equations: Langmuir, Freudlinch, Redlich-Peterson, Temkin, Dubinin-Radushkevich and Sips isotherms and it was found that the data fitted well with Sips isotherm model. The study showed that the process depends on current density, temperature, pH and initial dye concentration. The calculated thermodynamics parameters (Δ G°, Δ H° and Δ S°) indicated that the process is spontaneous and endothermic in nature.

Changes in assembly processes in soil bacterial communities following a wildfire disturbance.

PubMed

Ferrenberg, Scott; O'Neill, Sean P; Knelman, Joseph E; Todd, Bryan; Duggan, Sam; Bradley, Daniel; Robinson, Taylor; Schmidt, Steven K; Townsend, Alan R; Williams, Mark W; Cleveland, Cory C; Melbourne, Brett A; Jiang, Lin; Nemergut, Diana R

2013-06-01

Although recent work has shown that both deterministic and stochastic processes are important in structuring microbial communities, the factors that affect the relative contributions of niche and neutral processes are poorly understood. The macrobiological literature indicates that ecological disturbances can influence assembly processes. Thus, we sampled bacterial communities at 4 and 16 weeks following a wildfire and used null deviation analysis to examine the role that time since disturbance has in community assembly. Fire dramatically altered bacterial community structure and diversity as well as soil chemistry for both time-points. Community structure shifted between 4 and 16 weeks for both burned and unburned communities. Community assembly in burned sites 4 weeks after fire was significantly more stochastic than in unburned sites. After 16 weeks, however, burned communities were significantly less stochastic than unburned communities. Thus, we propose a three-phase model featuring shifts in the relative importance of niche and neutral processes as a function of time since disturbance. Because neutral processes are characterized by a decoupling between environmental parameters and community structure, we hypothesize that a better understanding of community assembly may be important in determining where and when detailed studies of community composition are valuable for predicting ecosystem function.

Changes in assembly processes in soil bacterial communities following a wildfire disturbance

PubMed Central

Ferrenberg, Scott; O'Neill, Sean P; Knelman, Joseph E; Todd, Bryan; Duggan, Sam; Bradley, Daniel; Robinson, Taylor; Schmidt, Steven K; Townsend, Alan R; Williams, Mark W; Cleveland, Cory C; Melbourne, Brett A; Jiang, Lin; Nemergut, Diana R

2013-01-01

Although recent work has shown that both deterministic and stochastic processes are important in structuring microbial communities, the factors that affect the relative contributions of niche and neutral processes are poorly understood. The macrobiological literature indicates that ecological disturbances can influence assembly processes. Thus, we sampled bacterial communities at 4 and 16 weeks following a wildfire and used null deviation analysis to examine the role that time since disturbance has in community assembly. Fire dramatically altered bacterial community structure and diversity as well as soil chemistry for both time-points. Community structure shifted between 4 and 16 weeks for both burned and unburned communities. Community assembly in burned sites 4 weeks after fire was significantly more stochastic than in unburned sites. After 16 weeks, however, burned communities were significantly less stochastic than unburned communities. Thus, we propose a three-phase model featuring shifts in the relative importance of niche and neutral processes as a function of time since disturbance. Because neutral processes are characterized by a decoupling between environmental parameters and community structure, we hypothesize that a better understanding of community assembly may be important in determining where and when detailed studies of community composition are valuable for predicting ecosystem function. PMID:23407312

Reduction of tablet weight variability by optimizing paddle speed in the forced feeder of a high-speed rotary tablet press.

PubMed

Peeters, Elisabeth; De Beer, Thomas; Vervaet, Chris; Remon, Jean-Paul

2015-04-01

Tableting is a complex process due to the large number of process parameters that can be varied. Knowledge and understanding of the influence of these parameters on the final product quality is of great importance for the industry, allowing economic efficiency and parametric release. The aim of this study was to investigate the influence of paddle speeds and fill depth at different tableting speeds on the weight and weight variability of tablets. Two excipients possessing different flow behavior, microcrystalline cellulose (MCC) and dibasic calcium phosphate dihydrate (DCP), were selected as model powders. Tablets were manufactured via a high-speed rotary tablet press using design of experiments (DoE). During each experiment also the volume of powder in the forced feeder was measured. Analysis of the DoE revealed that paddle speeds are of minor importance for tablet weight but significantly affect volume of powder inside the feeder in case of powders with excellent flowability (DCP). The opposite effect of paddle speed was observed for fairly flowing powders (MCC). Tableting speed played a role in weight and weight variability, whereas changing fill depth exclusively influenced tablet weight. The DoE approach allowed predicting the optimum combination of process parameters leading to minimum tablet weight variability. Monte Carlo simulations allowed assessing the probability to exceed the acceptable response limits if factor settings were varied around their optimum. This multi-dimensional combination and interaction of input variables leading to response criteria with acceptable probability reflected the design space.

Optimization of Process Parameters of Pulsed Electro Deposition Technique for Nanocrystalline Nickel Coating Using Gray Relational Analysis (GRA)

NASA Astrophysics Data System (ADS)

Venkatesh, C.; Sundara Moorthy, N.; Venkatesan, R.; Aswinprasad, V.

The moving parts of any mechanism and machine parts are always subjected to a significant wear due to the development of friction. It is an utmost important aspect to address the wear problems in present environment. But the complexity goes on increasing to replace the worn out parts if they are very precise. Technology advancement in surface engineering ensures the minimum surface wear with the introduction of polycrystalline nano nickel coating. The enhanced tribological property of the nano nickel coating was achieved by the development of grain size and hardness of the surface. In this study, it has been decided to focus on the optimized parameters of the pulsed electro deposition to develop such a coating. Taguchi’s method coupled gray relational analysis was employed by considering the pulse frequency, average current density and duty cycle as the chief process parameters. The grain size and hardness were considered as responses. Totally, nine experiments were conducted as per L9 design of experiment. Additionally, response graph method has been applied to determine the most significant parameter to influence both the responses. In order to improve the degree of validation, confirmation test and predicted gray grade were carried out with the optimized parameters. It has been observed that there was significant improvement in gray grade for the optimal parameters.

Global sensitivity and uncertainty analysis of the nitrate leaching and crop yield simulation under different water and nitrogen management practices

USDA-ARS?s Scientific Manuscript database

Agricultural system models have become important tools in studying water and nitrogen (N) dynamics, as well as crop growth, under different management practices. Complexity in input parameters often leads to significant uncertainty when simulating dynamic processes such as nitrate leaching or crop y...

A Model Fit Statistic for Generalized Partial Credit Model

ERIC Educational Resources Information Center

Liang, Tie; Wells, Craig S.

2009-01-01

Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…

Computerized Simulation in the Social Sciences: A Survey and Evaluation

ERIC Educational Resources Information Center

Garson, G. David

2009-01-01

After years at the periphery of the social sciences, simulation is now emerging as an important and widely used tool for understanding social phenomena. Through simulation, researchers can identify causal effects, specify critical parameter estimates, and clarify the state of the art with respect to what is understood about how processes evolve…

Mango (Mangifera indica L.) cv. Kent fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening

USDA-ARS?s Scientific Manuscript database

Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. "K...

The effect of varieties on cotton wax as it relates to cotton quality parameters

USDA-ARS?s Scientific Manuscript database

Cotton wax is one of the non-cellulosic components found on the surfaces of cotton. It is important in dyeing and processing quality. This investigation was carried out to study the yield of wax on the surface of cottons by performing two methods: Soxhlet extractions and accelerated solvent extracti...

Fitting-free algorithm for efficient quantification of collagen fiber alignment in SHG imaging applications.

PubMed

Hall, Gunnsteinn; Liang, Wenxuan; Li, Xingde

2017-10-01

Collagen fiber alignment derived from second harmonic generation (SHG) microscopy images can be important for disease diagnostics. Image processing algorithms are needed to robustly quantify the alignment in images with high sensitivity and reliability. Fourier transform (FT) magnitude, 2D power spectrum, and image autocorrelation have previously been used to extract fiber information from images by assuming a certain mathematical model (e.g. Gaussian distribution of the fiber-related parameters) and fitting. The fitting process is slow and fails to converge when the data is not Gaussian. Herein we present an efficient constant-time deterministic algorithm which characterizes the symmetricity of the FT magnitude image in terms of a single parameter, named the fiber alignment anisotropy R ranging from 0 (randomized fibers) to 1 (perfect alignment). This represents an important improvement of the technology and may bring us one step closer to utilizing the technology for various applications in real time. In addition, we present a digital image phantom-based framework for characterizing and validating the algorithm, as well as assessing the robustness of the algorithm against different perturbations.

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Prediction of plasma properties in mercury ion thrusters

NASA Technical Reports Server (NTRS)

Longhurst, G. R.

1978-01-01

A simplified theoretical model was developed which obtains to first order the plasma properties in the discharge chamber of a mercury ion thruster from basic thruster design and controllable operating parameters. The basic operation and design of ion thrusters is discussed, and the important processes which influence the plasma properties are described in terms of the design and control parameters. The conservation for mass, charge and energy were applied to the ion production region, which was defined as the region of the discharge chamber having as its outer boundary the surface of revolution of the innermost field line to intersect the anode. Mass conservation and the equations describing the various processes involved with mass addition and removal from the ion production region are satisfied by a Maxwellian electron density spatial distribution in that region.

Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

PubMed

Chandrasekaran, Sivapragasam; Sankararajan, Vanitha; Neelakandhan, Nampoothiri; Ram Kumar, Mahalakshmi

2017-11-04

This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (T w ), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (T atm ), wind speed (U w ), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (T a ). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

Mechanical performance and parameter sensitivity analysis of 3D braided composites joints.

PubMed

Wu, Yue; Nan, Bo; Chen, Liang

2014-01-01

3D braided composite joints are the important components in CFRP truss, which have significant influence on the reliability and lightweight of structures. To investigate the mechanical performance of 3D braided composite joints, a numerical method based on the microscopic mechanics is put forward, the modeling technologies, including the material constants selection, element type, grid size, and the boundary conditions, are discussed in detail. Secondly, a method for determination of ultimate bearing capacity is established, which can consider the strength failure. Finally, the effect of load parameters, geometric parameters, and process parameters on the ultimate bearing capacity of joints is analyzed by the global sensitivity analysis method. The results show that the main pipe diameter thickness ratio γ, the main pipe diameter D, and the braided angle α are sensitive to the ultimate bearing capacity N.

An improved model to estimate trapping parameters in polymeric materials and its application on normal and aged low-density polyethylenes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Ning, E-mail: nl4g12@soton.ac.uk; He, Miao; Alghamdi, Hisham

2015-08-14

Trapping parameters can be considered as one of the important attributes to describe polymeric materials. In the present paper, a more accurate charge dynamics model has been developed, which takes account of charge dynamics in both volts-on and off stage into simulation. By fitting with measured charge data with the highest R-square value, trapping parameters together with injection barrier of both normal and aged low-density polyethylene samples were estimated using the improved model. The results show that, after long-term ageing process, the injection barriers of both electrons and holes is lowered, overall trap depth is shallower, and trap density becomesmore » much greater. Additionally, the changes in parameters for electrons are more sensitive than those of holes after ageing.« less

The remote supervisory and controlling experiment system of traditional Chinese medicine production based on Fieldbus

NASA Astrophysics Data System (ADS)

Zhan, Jinliang; Lu, Pei

2006-11-01

Since the quality of traditional Chinese medicine products are affected by raw material, machining and many other factors, it is difficult for traditional Chinese medicine production process especially the extracting process to ensure the steady and homogeneous quality. At the same time, there exist some quality control blind spots due to lacking on-line quality detection means. But if infrared spectrum analysis technology was used in traditional Chinese medicine production process on the basis of off-line analysis to real-time detect the quality of semi-manufactured goods and to be assisted by advanced automatic control technique, the steady and homogeneous quality can be obtained. It can be seen that the on-line detection of extracting process plays an important role in the development of Chinese patent medicines industry. In this paper, the design and implement of a traditional Chinese medicine extracting process monitoring experiment system which is based on PROFIBUS-DP field bus, OPC, and Internet technology is introduced. The system integrates intelligence node which gathering data, superior sub-system which achieving figure configuration and remote supervisory, during the process of traditional Chinese medicine production, monitors the temperature parameter, pressure parameter, quality parameter etc. And it can be controlled by the remote nodes in the VPN (Visual Private Network). Experiment and application do have proved that the system can reach the anticipation effect fully, and with the merits of operational stability, real-time, reliable, convenient and simple manipulation and so on.

A combined model of heat and mass transfer for the in situ extraction of volatile water from lunar regolith

NASA Astrophysics Data System (ADS)

Reiss, P.

2018-05-01

Chemical analysis of lunar soil samples often involves thermal processing to extract their volatile constituents, such as loosely adsorbed water. For the characterization of volatiles and their bonding mechanisms it is important to determine their desorption temperature. However, due to the low thermal diffusivity of lunar regolith, it might be difficult to reach a uniform heat distribution in a sample that is larger than only a few particles. Furthermore, the mass transport through such a sample is restricted, which might lead to a significant delay between actual desorption and measurable outgassing of volatiles from the sample. The entire volatiles extraction process depends on the dynamically changing heat and mass transfer within the sample, and is influenced by physical parameters such as porosity, tortuosity, gas density, temperature and pressure. To correctly interpret measurements of the extracted volatiles, it is important to understand the interaction between heat transfer, sorption, and gas transfer through the sample. The present paper discusses the molecular kinetics and mechanisms that are involved in the thermal extraction process and presents a combined parametrical computation model to simulate this process. The influence of water content on the gas diffusivity and thermal diffusivity is discussed and the issue of possible resorption of desorbed molecules within the sample is addressed. Based on the multi-physical computation model, a case study for the ProSPA instrument for in situ analysis of lunar volatiles is presented, which predicts relevant dynamic process parameters, such as gas pressure and process duration.

Characterization methods for liquid interfacial layers

NASA Astrophysics Data System (ADS)

Javadi, A.; Mucic, N.; Karbaschi, M.; Won, J. Y.; Lotfi, M.; Dan, A.; Ulaganathan, V.; Gochev, G.; Makievski, A. V.; Kovalchuk, V. I.; Kovalchuk, N. M.; Krägel, J.; Miller, R.

2013-05-01

Liquid interfaces are met everywhere in our daily life. The corresponding interfacial properties and their modification play an important role in many modern technologies. Most prominent examples are all processes involved in the formation of foams and emulsions, as they are based on a fast creation of new surfaces, often of an immense extension. During the formation of an emulsion, for example, all freshly created and already existing interfaces are permanently subject to all types of deformation. This clearly entails the need of a quantitative knowledge on relevant dynamic interfacial properties and their changes under conditions pertinent to the technological processes. We report on the state of the art of interfacial layer characterization, including the determination of thermodynamic quantities as base line for a further quantitative analysis of the more important dynamic interfacial characteristics. Main focus of the presented work is on the experimental possibilities available at present to gain dynamic interfacial parameters, such as interfacial tensions, adsorbed amounts, interfacial composition, visco-elastic parameters, at shortest available surface ages and fastest possible interfacial perturbations. The experimental opportunities are presented along with examples for selected systems and theoretical models for a best data analysis. We also report on simulation results and concepts of necessary refinements and developments in this important field of interfacial dynamics.

A new supernova light curve modeling program

NASA Astrophysics Data System (ADS)

Jäger, Zoltán; Nagy, Andrea P.; Biro, Barna I.; Vinkó, József

2017-12-01

Supernovae are extremely energetic explosions that highlight the violent deaths of various types of stars. Studying such cosmic explosions may be important because of several reasons. Supernovae play a key role in cosmic nucleosynthesis processes, and they are also the anchors of methods of measuring extragalactic distances. Several exotic physical processes take place in the expanding ejecta produced by the explosion. We have developed a fast and simple semi-analytical code to model the the light curve of core collapse supernovae. This allows the determination of their most important basic physical parameters, like the the radius of the progenitor star, the mass of the ejected envelope, the mass of the radioactive nickel synthesized during the explosion, among others.

Laboratory Studies of Heterogeneous Chemical Processes of Atmospheric Importance

NASA Technical Reports Server (NTRS)

Molina, Mario J.

2003-01-01

The objective of this study is to conduct measurements of chemical kinetics parameters for heterogeneous reactions of importance in the stratosphere and the troposphere. It involves the elucidation of the mechanism of the interaction of HC1 vapor with ice surfaces, which is the first step in the heterogeneous chlorine activation processes, as well as the investigation of the atmospheric oxidation mechanism of soot particles emitted by biomass and fossil fuels. The techniques being employed include turbulent flow- chemical ionization mass spectrometry and optical ellipsometry, among others. The next section summarizes our research activities during the first year of the project, and the section that follows consists of the statement of work for the second year.

Experimental Investigation of Thermal Conductivity of Meat During Freezing

NASA Astrophysics Data System (ADS)

Shinbayeva, A.; Arkharov, I.; Aldiyarov, A.; Drobyshev, A.; Zhubaniyazova, M.; Kurnosov, V.

2017-04-01

The cryogenic technologies of processing and storage of agricultural products are becoming increasingly indispensable in the food industry as an important factor of ensuring food safety. One of such technologies is the shock freezing of meat, which provides a higher degree of preservation of the quality of frozen products in comparison with traditional technologies. The thermal conductivity of meat is an important parameter influencing the energy consumption in the freezing process. This paper presents the results of an experimental investigation of the temperature dependence of the thermal conductivity of beef. The measurements were taken by using a specially designed measurement cell, which allows covering the temperature range from 80 to 300 K.

The External Quality Assessment Scheme (EQAS): Experiences of a medium sized accredited laboratory.

PubMed

Bhat, Vivek; Chavan, Preeti; Naresh, Chital; Poladia, Pratik

2015-06-15

We put forth our experiences of EQAS, analyzed the result discrepancies, reviewed the corrective actions and also put forth strategies for risk identification and prevention of potential errors in a medical laboratory. For hematology, EQAS samples - blood, peripheral and reticulocyte smears - were received quarterly every year. All the blood samples were processed on HMX hematology analyzer by Beckman-Coulter. For clinical chemistry, lyophilized samples were received and were processed on Siemens Dimension Xpand and RXL analyzers. For microbiology, EQAS samples were received quarterly every year as lyophilized strains along with smears and serological samples. In hematology no outliers were noted for reticulocyte and peripheral smear examination. Only one outlier was noted for CBC. In clinical chemistry outliers (SDI ≥ 2) were noted in 7 samples (23 parameters) out of total 36 samples (756 parameters) processed. Thirteen of these parameters were analyzed as random errors, 3 as transcriptional errors and seven instances of systemic error were noted. In microbiology, one discrepancy was noted in isolate identification and in the grading of smears for AFB by Ziehl Neelsen stain. EQAS along with IQC is a very important tool for maintaining optimal quality of services. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of analysis technique to predict the material behavior of blowing agent

NASA Astrophysics Data System (ADS)

Hwang, Ji Hoon; Lee, Seonggi; Hwang, So Young; Kim, Naksoo

2014-11-01

In order to numerically simulate the foaming behavior of mastic sealer containing the blowing agent, a foaming and driving force model are needed which incorporate the foaming characteristics. Also, the elastic stress model is required to represent the material behavior of co-existing phase of liquid state and the cured polymer. It is important to determine the thermal properties such as thermal conductivity and specific heat because foaming behavior is heavily influenced by temperature change. In this study, three models are proposed to explain the foaming process and material behavior during and after the process. To obtain the material parameters in each model, following experiments and the numerical simulations are performed: thermal test, simple shear test and foaming test. The error functions are defined as differences between the experimental measurements and the numerical simulation results, and then the parameters are determined by minimizing the error functions. To ensure the validity of the obtained parameters, the confirmation simulation for each model is conducted by applying the determined parameters. The cross-verification is performed by measuring the foaming/shrinkage force. The results of cross-verification tended to follow the experimental results. Interestingly, it was possible to estimate the micro-deformation occurring in automobile roof surface by applying the proposed model to oven process analysis. The application of developed analysis technique will contribute to the design with minimized micro-deformation.

Discharge runaway in high power impulse magnetron sputtering of carbon: the effect of gas pressure, composition and target peak voltage

NASA Astrophysics Data System (ADS)

Vitelaru, Catalin; Aijaz, Asim; Constantina Parau, Anca; Kiss, Adrian Emil; Sobetkii, Arcadie; Kubart, Tomas

2018-04-01

Pressure and target voltage driven discharge runaway from low to high discharge current density regimes in high power impulse magnetron sputtering of carbon is investigated. The main purpose is to provide a meaningful insight of the discharge dynamics, with the ultimate goal to establish a correlation between discharge properties and process parameters to control the film growth. This is achieved by examining a wide range of pressures (2–20 mTorr) and target voltages (700–850 V) and measuring ion saturation current density at the substrate position. We show that the minimum plasma impedance is an important parameter identifying the discharge transition as well as establishing a stable operating condition. Using the formalism of generalized recycling model, we introduce a new parameter, ‘recycling ratio’, to quantify the process gas recycling for specific process conditions. The model takes into account the ion flux to the target, the amount of gas available, and the amount of gas required for sustaining the discharge. We show that this parameter describes the relation between the gas recycling and the discharge current density. As a test case, we discuss the pressure and voltage driven transitions by changing the gas composition when adding Ne into the discharge. We propose that standard Ar HiPIMS discharges operated with significant gas recycling do not require Ne to increase the carbon ionization.

Colloidal Fouling of Nanofiltration Membranes: Development of a Standard Operating Procedure

PubMed Central

Al Mamun, Md Abdullaha; Bhattacharjee, Subir; Pernitsky, David; Sadrzadeh, Mohtada

2017-01-01

Fouling of nanofiltration (NF) membranes is the most significant obstacle to the development of a sustainable and energy-efficient NF process. Colloidal fouling and performance decline in NF processes is complex due to the combination of cake formation and salt concentration polarization effects, which are influenced by the properties of the colloids and the membrane, the operating conditions of the test, and the solution chemistry. Although numerous studies have been conducted to investigate the influence of these parameters on the performance of the NF process, the importance of membrane preconditioning (e.g., compaction and equilibrating with salt water), as well as the determination of key parameters (e.g., critical flux and trans-membrane osmotic pressure) before the fouling experiment have not been reported in detail. The aim of this paper is to present a standard experimental and data analysis protocol for NF colloidal fouling experiments. The developed methodology covers preparation and characterization of water samples and colloidal particles, pre-test membrane compaction and critical flux determination, measurement of experimental data during the fouling test, and the analysis of that data to determine the relative importance of various fouling mechanisms. The standard protocol is illustrated with data from a series of flat sheet, bench-scale experiments. PMID:28106775

A parametric numerical study of mixing in a cylindrical duct

NASA Astrophysics Data System (ADS)

Oechsle, V. L.; Mongia, H. C.; Holderman, J. D.

1992-07-01

The interaction is described of some of the important parameters affecting the mixing process in a quick mixing region of a rich burn/quick mix/lean burn (RQL) combustor. The performance of the quick mixing region is significantly affected by the geometric designs of both the mixing domain and the jet inlet orifices. Several of the important geometric parameters and operating conditions affecting the mixing process were analytically studied. Parameters such as jet-to-mainstream momentum flux ratio (J), mass flow ratio (MR), orifice geometry, orifice orientation, and number of orifices/row (equally spaced around the circumferential direction were analyzed. Three different sets of orifice shapes were studied: (1) square, (2) elongated slots, and (3) equilateral triangles. Based on the analytical results, the best mixing configuration depends significantly on the penetration depth of the jet to prevent the hot mainstream flow from being entrained behind the orifice. The structure in a circular mixing section is highly weighted toward the outer wall and any mixing structure affecting this area significantly affects the overall results. The increase in the number of orifices per row increases the mixing at higher J conditions. Higher slot slant angles and aspect ratios are generally the best mixing configurations at higher momentum flux ratio (J) conditions. However, the square and triangular shaped orifices were more effective mixing configurations at lower J conditions.

X-ray Computed Tomography Assessment of Air Void Distribution in Concrete

NASA Astrophysics Data System (ADS)

Lu, Haizhu

Air void size and spatial distribution have long been regarded as critical parameters in the frost resistance of concrete. In cement-based materials, entrained air void systems play an important role in performance as related to durability, permeability, and heat transfer. Many efforts have been made to measure air void parameters in a more efficient and reliable manner in the past several decades. Standardized measurement techniques based on optical microscopy and stereology on flat cut and polished surfaces are widely used in research as well as in quality assurance and quality control applications. Other more automated methods using image processing have also been utilized, but still starting from flat cut and polished surfaces. The emergence of X-ray computed tomography (CT) techniques provides the capability of capturing the inner microstructure of materials at the micrometer and nanometer scale. X-ray CT's less demanding sample preparation and capability to measure 3D distributions of air voids directly provide ample prospects for its wider use in air void characterization in cement-based materials. However, due to the huge number of air voids that can exist within a limited volume, errors can easily arise in the absence of a formalized data processing procedure. In this study, air void parameters in selected types of cement-based materials (lightweight concrete, structural concrete elements, pavements, and laboratory mortars) have been measured using micro X-ray CT. The focus of this study is to propose a unified procedure for processing the data and to provide solutions to deal with common problems that arise when measuring air void parameters: primarily the reliable segmentation of objects of interest, uncertainty estimation of measured parameters, and the comparison of competing segmentation parameters.

A New Polar Magnetic Index of Geomagnetic Activity and its Application to Monitoring Ionospheric Parameters

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

For improving the reliability of Space Weather prediction, we developed a new, Polar Magnetic (PM) index of geomagnetic activity, which shows high correlation with both upstream solar wind data and related events in the magnetosphere and ionosphere. Similarly to the existing polar cap PC index, the new, PM index was computed from data from two near-pole geomagnetic observatories; however, the method for computing the PM index is different. The high correlation of the PM index with both solar wind data and events in Geospace environment makes possible to improve significantly forecasting geomagnetic disturbances and such important parameters as the cross-polar-cap voltage and global Joule heating in high latitude ionosphere, which play an important role in the development of geomagnetic, ionospheric and thermospheric disturbances. We tested the PM index for 10-year period (1995-2004). The correlation between PM index and upstream solar wind data for these years is very high (the average correlation coefficient R approximately equal to 0.86). The PM index also shows the high correlation with the cross-polar-cap voltage and hemispheric Joule heating (the correlation coefficient between the actual and predicted values of these parameters is approximately 0.9), which results in significant increasing the prediction reliability of these parameters. Using the PM index of geomagnetic activity provides a significant increase in the forecasting reliability of geomagnetic disturbances and related events in Geospace environment. The PM index may be also used as an important input parameter in modeling ionospheric, magnetospheric, and thermospheric processes.

Acute effect of Vagus nerve stimulation parameters on cardiac chronotropic, inotropic, and dromotropic responses

NASA Astrophysics Data System (ADS)

Ojeda, David; Le Rolle, Virginie; Romero-Ugalde, Hector M.; Gallet, Clément; Bonnet, Jean-Luc; Henry, Christine; Bel, Alain; Mabo, Philippe; Carrault, Guy; Hernández, Alfredo I.

2017-11-01

Vagus nerve stimulation (VNS) is an established therapy for drug-resistant epilepsy and depression, and is considered as a potential therapy for other pathologies, including Heart Failure (HF) or inflammatory diseases. In the case of HF, several experimental studies on animals have shown an improvement in the cardiac function and a reverse remodeling of the cardiac cavity when VNS is applied. However, recent clinical trials have not been able to reproduce the same response in humans. One of the hypothesis to explain this lack of response is related to the way in which stimulation parameters are defined. The combined effect of VNS parameters is still poorly-known, especially in the case of VNS synchronously delivered with cardiac activity. In this paper, we propose a methodology to analyze the acute cardiovascular effects of VNS parameters individually, as well as their interactive effects. A Latin hypercube sampling method was applied to design a uniform experimental plan. Data gathered from this experimental plan was used to produce a Gaussian process regression (GPR) model in order to estimate unobserved VNS sequences. Finally, a Morris screening sensitivity analysis method was applied to each obtained GPR model. Results highlight dominant effects of pulse current, pulse width and number of pulses over frequency and delay and, more importantly, the degree of interactions between these parameters on the most important acute cardiovascular responses. In particular, high interacting effects between current and pulse width were found. Similar sensitivity profiles were observed for chronotropic, dromotropic and inotropic effects. These findings are of primary importance for the future development of closed-loop, personalized neuromodulator technologies.

A computational model for biosonar echoes from foliage

PubMed Central

Gupta, Anupam Kumar; Lu, Ruijin; Zhu, Hongxiao

2017-01-01

Since many bat species thrive in densely vegetated habitats, echoes from foliage are likely to be of prime importance to the animals’ sensory ecology, be it as clutter that masks prey echoes or as sources of information about the environment. To better understand the characteristics of foliage echoes, a new model for the process that generates these signals has been developed. This model takes leaf size and orientation into account by representing the leaves as circular disks of varying diameter. The two added leaf parameters are of potential importance to the sensory ecology of bats, e.g., with respect to landmark recognition and flight guidance along vegetation contours. The full model is specified by a total of three parameters: leaf density, average leaf size, and average leaf orientation. It assumes that all leaf parameters are independently and identically distributed. Leaf positions were drawn from a uniform probability density function, sizes and orientations each from a Gaussian probability function. The model was found to reproduce the first-order amplitude statistics of measured example echoes and showed time-variant echo properties that depended on foliage parameters. Parameter estimation experiments using lasso regression have demonstrated that a single foliage parameter can be estimated with high accuracy if the other two parameters are known a priori. If only one parameter is known a priori, the other two can still be estimated, but with a reduced accuracy. Lasso regression did not support simultaneous estimation of all three parameters. Nevertheless, these results demonstrate that foliage echoes contain accessible information on foliage type and orientation that could play a role in supporting sensory tasks such as landmark identification and contour following in echolocating bats. PMID:28817631

A computational model for biosonar echoes from foliage.

PubMed

Ming, Chen; Gupta, Anupam Kumar; Lu, Ruijin; Zhu, Hongxiao; Müller, Rolf

2017-01-01

Since many bat species thrive in densely vegetated habitats, echoes from foliage are likely to be of prime importance to the animals' sensory ecology, be it as clutter that masks prey echoes or as sources of information about the environment. To better understand the characteristics of foliage echoes, a new model for the process that generates these signals has been developed. This model takes leaf size and orientation into account by representing the leaves as circular disks of varying diameter. The two added leaf parameters are of potential importance to the sensory ecology of bats, e.g., with respect to landmark recognition and flight guidance along vegetation contours. The full model is specified by a total of three parameters: leaf density, average leaf size, and average leaf orientation. It assumes that all leaf parameters are independently and identically distributed. Leaf positions were drawn from a uniform probability density function, sizes and orientations each from a Gaussian probability function. The model was found to reproduce the first-order amplitude statistics of measured example echoes and showed time-variant echo properties that depended on foliage parameters. Parameter estimation experiments using lasso regression have demonstrated that a single foliage parameter can be estimated with high accuracy if the other two parameters are known a priori. If only one parameter is known a priori, the other two can still be estimated, but with a reduced accuracy. Lasso regression did not support simultaneous estimation of all three parameters. Nevertheless, these results demonstrate that foliage echoes contain accessible information on foliage type and orientation that could play a role in supporting sensory tasks such as landmark identification and contour following in echolocating bats.

Collisional excitation of CO by H2O - An astrophysicist's guide to obtaining rate constants from coherent anti-Stokes Raman line shape data

NASA Technical Reports Server (NTRS)

Green, Sheldon

1993-01-01

Rate constants for excitation of CO by collisions with H2O are needed to understand recent observations of comet spectra. These collision rates are closely related to spectral line shape parameters, especially those for Raman Q-branch spectra. Because such spectra have become quite important for thermometry applications, much effort has been invested in understanding this process. Although it is not generally possible to extract state-to-state rate constants directly from the data as there are too many unknowns, if the matrix of state-to-state rates can be expressed in terms of a rate-law model which depends only on rotational quantum numbers plus a few parameters, the parameters can be determined from the data; this has been done with some success for many systems, especially those relevant to combustion processes. Although such an analysis has not yet been done for CO-H2O, this system is expected to behave similarly to N2-H2O which has been well studies; modifications of parameters for the latter system are suggested which should provide a reasonable description of rate constants for the former.

Influence of ionospheric disturbances onto long-baseline relative positioning in kinematic mode

NASA Astrophysics Data System (ADS)

Wezka, Kinga; Herrera, Ivan; Cokrlic, Marija; Galas, Roman

2013-04-01

Ionospheric disturbances are fast and random variabilities in the ionosphere and they are difficult to detect and model. Some strong disturbances can cause, among others, interruption of GNSS signal or even lead to loss of signal lock. These phenomena are especially harmful for kinematic real-time applications, where the system availability is one of the most important parameters influencing positioning reliability. Our investigations were conducted using long time series of GNSS observations gathered at high latitude, where ionospheric disturbances more frequently occur. Selected processing strategy was used to monitor ionospheric signatures in time series of the coordinates. Quality of the data of input and of the processing results were examined and described by a set of proposed parameters. Variations in the coordinates were compared with available information about the state of ionosphere derived from Neustrelitz TEC Model (NTCM) and with the time series of raw observations. Some selected parameters were also calculated with the "iono-tools" module of the TUB-NavSolutions software developed by the Precise Navigation and Positioning Group at Technische Universitaet Berlin. The paper presents very first results of evaluation of the robustness of positioning algorithms with respect to ionospheric anomalies using the NTCM model and our calculated ionospheric parameters.

Classification of video sequences into chosen generalized use classes of target size and lighting level.

PubMed

Leszczuk, Mikołaj; Dudek, Łukasz; Witkowski, Marcin

The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage time-frame, discrimination level, target size, lighting level, and level of motion. These parameters form what are referred to as Generalized Use Classes (GUCs). The aim of our research was to develop algorithms that would automatically assist classification of input sequences into one of the GUCs. Target size and lighting level parameters were approached. The experiment described reveals the experts' ambiguity and hesitation during the manual target size determination process. However, the automatic methods developed for target size classification make it possible to determine GUC parameters with 70 % compliance to the end-users' opinion. Lighting levels of the entire sequence can be classified with an efficiency reaching 93 %. To make the algorithms available for use, a test application has been developed. It is able to process video files and display classification results, the user interface being very simple and requiring only minimal user interaction.

The Mathematics of Psychotherapy: A Nonlinear Model of Change Dynamics.

PubMed

Schiepek, Gunter; Aas, Benjamin; Viol, Kathrin

2016-07-01

Psychotherapy is a dynamic process produced by a complex system of interacting variables. Even though there are qualitative models of such systems the link between structure and function, between network and network dynamics is still missing. The aim of this study is to realize these links. The proposed model is composed of five state variables (P: problem severity, S: success and therapeutic progress, M: motivation to change, E: emotions, I: insight and new perspectives) interconnected by 16 functions. The shape of each function is modified by four parameters (a: capability to form a trustful working alliance, c: mentalization and emotion regulation, r: behavioral resources and skills, m: self-efficacy and reward expectation). Psychologically, the parameters play the role of competencies or traits, which translate into the concept of control parameters in synergetics. The qualitative model was transferred into five coupled, deterministic, nonlinear difference equations generating the dynamics of each variable as a function of other variables. The mathematical model is able to reproduce important features of psychotherapy processes. Examples of parameter-dependent bifurcation diagrams are given. Beyond the illustrated similarities between simulated and empirical dynamics, the model has to be further developed, systematically tested by simulated experiments, and compared to empirical data.

Experimental research of the influence of the strength of ore samples on the parameters of an electromagnetic signal during acoustic excitation in the process of uniaxial compression

NASA Astrophysics Data System (ADS)

Yavorovich, L. V.; Bespal`ko, A. A.; Fedotov, P. I.

2018-01-01

Parameters of electromagnetic responses (EMRe) generated during uniaxial compression of rock samples under excitation by deterministic acoustic pulses are presented and discussed. Such physical modeling in the laboratory allows to reveal the main regularities of electromagnetic signals (EMS) generation in rock massive. The influence of the samples mechanical properties on the parameters of the EMRe excited by an acoustic signal in the process of uniaxial compression is considered. It has been established that sulfides and quartz in the rocks of the Tashtagol iron ore deposit (Western Siberia, Russia) contribute to the conversion of mechanical energy into the energy of the electromagnetic field, which is expressed in an increase in the EMS amplitude. The decrease in the EMS amplitude when the stress-strain state of the sample changes during the uniaxial compression is observed when the amount of conductive magnetite contained in the rock is increased. The obtained results are important for the physical substantiation of testing methods and monitoring of changes in the stress-strain state of the rock massive by the parameters of electromagnetic signals and the characteristics of electromagnetic emission.

A deterministic (non-stochastic) low frequency method for geoacoustic inversion.

PubMed

Tolstoy, A

2010-06-01

It is well known that multiple frequency sources are necessary for accurate geoacoustic inversion. This paper presents an inversion method which uses the low frequency (LF) spectrum only to estimate bottom properties even in the presence of expected errors in source location, phone depths, and ocean sound-speed profiles. Matched field processing (MFP) along a vertical array is used. The LF method first conducts an exhaustive search of the (five) parameter search space (sediment thickness, sound-speed at the top of the sediment layer, the sediment layer sound-speed gradient, the half-space sound-speed, and water depth) at 25 Hz and continues by retaining only the high MFP value parameter combinations. Next, frequency is slowly increased while again retaining only the high value combinations. At each stage of the process, only those parameter combinations which give high MFP values at all previous LF predictions are considered (an ever shrinking set). It is important to note that a complete search of each relevant parameter space seems to be necessary not only at multiple (sequential) frequencies but also at multiple ranges in order to eliminate sidelobes, i.e., false solutions. Even so, there are no mathematical guarantees that one final, unique "solution" will be found.

Proton irradiation of simple gas mixtures: Influence of irradiation parameters

NASA Technical Reports Server (NTRS)

Sack, Norbert J.; Schuster, R.; Hofmann, A.

1990-01-01

In order to get information about the influence of irradiation parameters on radiolysis processes of astrophysical interest, methane gas targets were irradiated with 6.5 MeV protons at a pressure of 1 bar and room temperature. Yields of higher hydrocarbons like ethane or propane were found by analysis of irradiated gas samples using gas chromatography. The handling of the proton beam was of great experimental importance for determining the irradiation parameters. In a series of experiments current density of the proton beam and total absorbed energy were shown to have a large influence on the yields of produced hydrocarbons. Mechanistic interpretations of the results are given and conclusions are drawn with regard to the chemistry and the simulation of various astrophysical systems.

Study on Nonlinear Vibration Analysis of Gear System with Random Parameters

NASA Astrophysics Data System (ADS)

Tong, Cao; Liu, Xiaoyuan; Fan, Li

2018-03-01

In order to study the dynamic characteristics of gear nonlinear vibration system and the influence of random parameters, firstly, a nonlinear stochastic vibration analysis model of gear 3-DOF is established based on Newton’s Law. And the random response of gear vibration is simulated by stepwise integration method. Secondly, the influence of stochastic parameters such as meshing damping, tooth side gap and excitation frequency on the dynamic response of gear nonlinear system is analyzed by using the stability analysis method such as bifurcation diagram and Lyapunov exponent method. The analysis shows that the stochastic process can not be neglected, which can cause the random bifurcation and chaos of the system response. This study will provide important reference value for vibration engineering designers.

A novel spatter detection algorithm based on typical cellular neural network operations for laser beam welding processes

NASA Astrophysics Data System (ADS)

Nicolosi, L.; Abt, F.; Blug, A.; Heider, A.; Tetzlaff, R.; Höfler, H.

2012-01-01

Real-time monitoring of laser beam welding (LBW) has increasingly gained importance in several manufacturing processes ranging from automobile production to precision mechanics. In the latter, a novel algorithm for the real-time detection of spatters was implemented in a camera based on cellular neural networks. The latter can be connected to the optics of commercially available laser machines leading to real-time monitoring of LBW processes at rates up to 15 kHz. Such high monitoring rates allow the integration of other image evaluation tasks such as the detection of the full penetration hole for real-time control of process parameters.

Evidence of a two-step process and pathway dependency in the thermodynamics of poly(diallyldimethylammonium chloride)/poly(sodium acrylate) complexation.

PubMed

Vitorazi, L; Ould-Moussa, N; Sekar, S; Fresnais, J; Loh, W; Chapel, J-P; Berret, J-F

2014-12-21

Recent studies have pointed out the importance of polyelectrolyte assembly in the elaboration of innovative nanomaterials. Beyond their structures, many important questions on the thermodynamics of association remain unanswered. Here, we investigate the complexation between poly(diallyldimethylammonium chloride) (PDADMAC) and poly(sodium acrylate) (PANa) chains using a combination of three techniques: isothermal titration calorimetry (ITC), static and dynamic light scattering and electrophoresis. Upon addition of PDADMAC to PANa or vice-versa, the results obtained by the different techniques agree well with each other, and reveal a two-step process. The primary process is the formation of highly charged polyelectrolyte complexes of size 100 nm. The secondary process is the transition towards a coacervate phase made of rich and poor polymer droplets. The binding isotherms measured are accounted for using a phenomenological model that provides the thermodynamic parameters for each reaction. Small positive enthalpies and large positive entropies consistent with a counterion release scenario are found throughout this study. Furthermore, this work stresses the importance of the underestimated formulation pathway or mixing order in polyelectrolyte complexation.

Inactivation of Salmonella Senftenberg strain W 775 during composting of biowastes and garden wastes.

PubMed

Ceustermans, A; De Clercq, D; Aertsen, A; Michiels, C; Geeraerd, A; Van Impe, J; Coosemans, J; Ryckeboer, J

2007-07-01

Determination of the minimum requirements (time-temperature relationship and moisture content) that are needed for a sufficient eradication of an indicator organism. To determine the hygienic safety of composting processes, the indicator organism Salmonella enterica ssp. enterica serotype Senftenberg strain W 775 (further abbreviated as W 775) was artificially inoculated on a meat carrier and monitored subsequently. Different types of composting processes, e.g. composting in enclosed facilities, in open-air and in-vessel composting, were investigated. The waste feedstocks used in this work were either biowastes (i.e. vegetable, fruit and garden wastes; also called source-separated household wastes) or pure garden wastes. Beside these large-scale trials, we also conducted some lab experiments in order to determine the impact of temperature, moisture content and the presence of an indigenous microflora on the eradication of W 775. We found the temperature to be the most important parameter to eradicate W 775 from compost. When the temperature of the compost heap is 60 degrees C and the moisture content varies between 60-65%, W 775 (10(8) CFU g(-1)) will be inactivated within 10 h of composting. The moisture content is, beside temperature, a second parameter that influences the survival of W 775. When the water content of the composting materials or meat carriers is reduced, a higher survival rate of W 775 was observed (survival rate increases 0.5 log(10) unit when there is a reduction of 5% in moisture content). In addition, other parameters (such as microbial antagonism, toxic compounds, etc.) have an influence on the survival of W 775 as well. Our study demonstrates that all types of composting processes tested in this work were sufficient to eradicate W 775 providing that they are well managed in terms of temperature and moisture content. To give a better view on the parameters of importance for the eradication of W 775 during composting.

Experimental and numerical study on optimization of the single point incremental forming of AINSI 304L stainless steel sheet

NASA Astrophysics Data System (ADS)

Saidi, B.; Giraud-Moreau, L.; Cherouat, A.; Nasri, R.

2017-09-01

AINSI 304L stainless steel sheets are commonly formed into a variety of shapes for applications in the industrial, architectural, transportation and automobile fields, it’s also used for manufacturing of denture base. In the field of dentistry, there is a need for personalized devises that are custom made for the patient. The single point incremental forming process is highly promising in this area for manufacturing of denture base. The single point incremental forming process (ISF) is an emerging process based on the use of a spherical tool, which is moved along CNC controlled tool path. One of the major advantages of this process is the ability to program several punch trajectories on the same machine in order to obtain different shapes. Several applications of this process exist in the medical field for the manufacturing of personalized titanium prosthesis (cranial plate, knee prosthesis...) due to the need of product customization to each patient. The objective of this paper is to study the incremental forming of AISI 304L stainless steel sheets for future applications in the dentistry field. During the incremental forming process, considerable forces can occur. The control of the forming force is particularly important to ensure the safe use of the CNC milling machine and preserve the tooling and machinery. In this paper, the effect of four different process parameters on the maximum force is studied. The proposed approach consists in using an experimental design based on experimental results. An analysis of variance was conducted with ANOVA to find the input parameters allowing to minimize the maximum forming force. A numerical simulation of the incremental forming process is performed with the optimal input process parameters. Numerical results are compared with the experimental ones.

A Bayesian Network Based Global Sensitivity Analysis Method for Identifying Dominant Processes in a Multi-physics Model

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2016-12-01

Sensitivity analysis has been an important tool in groundwater modeling to identify the influential parameters. Among various sensitivity analysis methods, the variance-based global sensitivity analysis has gained popularity for its model independence characteristic and capability of providing accurate sensitivity measurements. However, the conventional variance-based method only considers uncertainty contribution of single model parameters. In this research, we extended the variance-based method to consider more uncertainty sources and developed a new framework to allow flexible combinations of different uncertainty components. We decompose the uncertainty sources into a hierarchical three-layer structure: scenario, model and parametric. Furthermore, each layer of uncertainty source is capable of containing multiple components. An uncertainty and sensitivity analysis framework was then constructed following this three-layer structure using Bayesian network. Different uncertainty components are represented as uncertain nodes in this network. Through the framework, variance-based sensitivity analysis can be implemented with great flexibility of using different grouping strategies for uncertainty components. The variance-based sensitivity analysis thus is improved to be able to investigate the importance of an extended range of uncertainty sources: scenario, model, and other different combinations of uncertainty components which can represent certain key model system processes (e.g., groundwater recharge process, flow reactive transport process). For test and demonstration purposes, the developed methodology was implemented into a test case of real-world groundwater reactive transport modeling with various uncertainty sources. The results demonstrate that the new sensitivity analysis method is able to estimate accurate importance measurements for any uncertainty sources which were formed by different combinations of uncertainty components. The new methodology can provide useful information for environmental management and decision-makers to formulate policies and strategies.

Systematic Parameterization, Storage, and Representation of Volumetric DICOM Data.

PubMed

Fischer, Felix; Selver, M Alper; Gezer, Sinem; Dicle, Oğuz; Hillen, Walter

Tomographic medical imaging systems produce hundreds to thousands of slices, enabling three-dimensional (3D) analysis. Radiologists process these images through various tools and techniques in order to generate 3D renderings for various applications, such as surgical planning, medical education, and volumetric measurements. To save and store these visualizations, current systems use snapshots or video exporting, which prevents further optimizations and requires the storage of significant additional data. The Grayscale Softcopy Presentation State extension of the Digital Imaging and Communications in Medicine (DICOM) standard resolves this issue for two-dimensional (2D) data by introducing an extensive set of parameters, namely 2D Presentation States (2DPR), that describe how an image should be displayed. 2DPR allows storing these parameters instead of storing parameter applied images, which cause unnecessary duplication of the image data. Since there is currently no corresponding extension for 3D data, in this study, a DICOM-compliant object called 3D presentation states (3DPR) is proposed for the parameterization and storage of 3D medical volumes. To accomplish this, the 3D medical visualization process is divided into four tasks, namely pre-processing, segmentation, post-processing, and rendering. The important parameters of each task are determined. Special focus is given to the compression of segmented data, parameterization of the rendering process, and DICOM-compliant implementation of the 3DPR object. The use of 3DPR was tested in a radiology department on three clinical cases, which require multiple segmentations and visualizations during the workflow of radiologists. The results show that 3DPR can effectively simplify the workload of physicians by directly regenerating 3D renderings without repeating intermediate tasks, increase efficiency by preserving all user interactions, and provide efficient storage as well as transfer of visualized data.

Quantifying Atmospheric Moist Processes from Earth Observations. Really?

NASA Astrophysics Data System (ADS)

Shepson, P. B.; Cambaliza, M. O. L.; Salmon, O. E.; Heimburger, A. M. F.; Davis, K. J.; Lauvaux, T.; McGowan, L. E.; Miles, N.; Richardson, S.; Sarmiento, D. P.; Hardesty, M.; Karion, A.; Sweeney, C.; Iraci, L. T.; Hillyard, P. W.; Podolske, J. R.; Gurney, K. R.; Patarasuk, R.; Razlivanov, I. N.; Song, Y.; O'Keeffe, D.; Turnbull, J. C.; Vimont, I.; Whetstone, J. R.; Possolo, A.; Prasad, K.; Lopez-Coto, I.

2014-12-01

The amount of water in the Earth's atmosphere is tiny compared to all other sources of water on our planet, fresh or otherwise. However, this tiny amount of water is fundamental to most aspects of human life. The tiny amount of water that cycles from the Earth's surface, through condensation into clouds in the atmosphere returning as precipitation falling is not only natures way of delivering fresh water to land-locked human societies but it also exerts a fundamental control on our climate system producing the most important feedbacks in the system. The representation of these processes in Earth system models contain many errors that produce well now biases in the hydrological cycle. Surprisingly the parameterizations of these important processes are not well validated with observations. Part of the reason for this situation stems from the fact that process evaluation is difficult to achieve on the global scale since it has commonly been assumed that the static observations available from snap-shots of individual parameters contain little information on processes. One of the successes of the A-Train has been the development of multi-parameter analysis based on the multi-sensor data produced by the satellite constellation. This has led to new insights on how water cycles through the Earth's atmosphere. Examples of these insights will be highlighted. It will be described how the rain formation process has been observed and how this has been used to constrain this process in models, with a huge impact. How these observations are beginning to reveal insights on deep convection and examples of the use these observations applied to models will also be highlighted as will the effects of aerosol on clouds on radiation.

Quantifying Atmospheric Moist Processes from Earth Observations. Really?

NASA Astrophysics Data System (ADS)

Stephens, G. L.

2015-12-01

The amount of water in the Earth's atmosphere is tiny compared to all other sources of water on our planet, fresh or otherwise. However, this tiny amount of water is fundamental to most aspects of human life. The tiny amount of water that cycles from the Earth's surface, through condensation into clouds in the atmosphere returning as precipitation falling is not only natures way of delivering fresh water to land-locked human societies but it also exerts a fundamental control on our climate system producing the most important feedbacks in the system. The representation of these processes in Earth system models contain many errors that produce well now biases in the hydrological cycle. Surprisingly the parameterizations of these important processes are not well validated with observations. Part of the reason for this situation stems from the fact that process evaluation is difficult to achieve on the global scale since it has commonly been assumed that the static observations available from snap-shots of individual parameters contain little information on processes. One of the successes of the A-Train has been the development of multi-parameter analysis based on the multi-sensor data produced by the satellite constellation. This has led to new insights on how water cycles through the Earth's atmosphere. Examples of these insights will be highlighted. It will be described how the rain formation process has been observed and how this has been used to constrain this process in models, with a huge impact. How these observations are beginning to reveal insights on deep convection and examples of the use these observations applied to models will also be highlighted as will the effects of aerosol on clouds on radiation.

One-step patterning of double tone high contrast and high refractive index inorganic spin-on resist

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zanchetta, E.; Della Giustina, G.; Brusatin, G.

2014-09-14

A direct one-step and low temperature micro-fabrication process, enabling to realize large area totally inorganic TiO₂ micro-patterns from a spin-on resist, is presented. High refractive index structures (up to 2 at 632 nm) without the need for transfer processes have been obtained by mask assisted UV lithography, exploiting photocatalytic titania properties. A distinctive feature not shared by any of the known available resists and boosting the material versatility, is that the system behaves either as a positive or as negative tone resist, depending on the process parameters and on the development chemistry. In order to explain the resist double tonemore » behavior, deep comprehension of the lithographic process parameters optimization and of the resist chemistry and structure evolution during the lithographic process, generally uncommon in literature, is reported. Another striking property of the presented resist is that the negative tone shows a high contrast up to 19, allowing to obtain structures resolution down to 2 μm wide. The presented process and material permit to directly fabricate different titania geometries of great importance for solar cells, photo-catalysis, and photonic crystals applications.« less

Growth kinetics of vertically aligned carbon nanotube arrays in clean oxygen-free conditions.

PubMed

In, Jung Bin; Grigoropoulos, Costas P; Chernov, Alexander A; Noy, Aleksandr

2011-12-27

Vertically aligned carbon nanotubes (CNTs) are an important technological system, as well as a fascinating system for studying basic principles of nanomaterials synthesis; yet despite continuing efforts for the past decade many important questions about this process remain largely unexplained. We present a series of parametric ethylene chemical vapor deposition growth studies in a "hot-wall" reactor using ultrapure process gases that reveal the fundamental kinetics of the CNT growth. Our data show that the growth rate is proportional to the concentration of the carbon feedstock and monotonically decreases with the concentration of hydrogen gas and that the most important parameter determining the rate of the CNT growth is the production rate of active carbon precursor in the gas phase reaction. The growth termination times obtained with the purified gas mixtures were strikingly insensitive to variations in both hydrogen and ethylene pressures ruling out the carbon encapsulation of the catalyst as the main process termination cause.

A new methodology based on sensitivity analysis to simplify the recalibration of functional-structural plant models in new conditions.

PubMed

Mathieu, Amélie; Vidal, Tiphaine; Jullien, Alexandra; Wu, QiongLi; Chambon, Camille; Bayol, Benoit; Cournède, Paul-Henry

2018-06-19

Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.

The Development of a Microbial Challenge Test with Acholeplasma laidlawii To Rate Mycoplasma-Retentive Filters by Filter Manufacturers.

PubMed

Folmsbee, Martha; Lentine, Kerry Roche; Wright, Christine; Haake, Gerhard; Mcburnie, Leesa; Ashtekar, Dilip; Beck, Brian; Hutchison, Nick; Okhio-Seaman, Laura; Potts, Barbara; Pawar, Vinayak; Windsor, Helena

2014-01-01

Mycoplasma are bacteria that can penetrate 0.2 and 0.22 μm rated sterilizing-grade filters and even some 0.1 μm rated filters. Primary applications for mycoplasma filtration include large scale mammalian and bacterial cell culture media and serum filtration. The Parenteral Drug Association recognized the absence of standard industry test parameters for testing and classifying 0.1 μm rated filters for mycoplasma clearance and formed a task force to formulate consensus test parameters. The task force established some test parameters by common agreement, based upon general industry practices, without the need for additional testing. However, the culture medium and incubation conditions, for generating test mycoplasma cells, varied from filter company to filter company and was recognized as a serious gap by the task force. Standardization of the culture medium and incubation conditions required collaborative testing in both commercial filter company laboratories and in an Independent laboratory (Table I). The use of consensus test parameters will facilitate the ultimate cross-industry goal of standardization of 0.1 μm filter claims for mycoplasma clearance. However, it is still important to recognize filter performance will depend on the actual conditions of use. Therefore end users should consider, using a risk-based approach, whether process-specific evaluation of filter performance may be warranted for their application. Mycoplasma are small bacteria that have the ability to penetrate sterilizing-grade filters. Filtration of large-scale mammalian and bacterial cell culture media is an example of an industry process where effective filtration of mycoplasma is required. The Parenteral Drug Association recognized the absence of industry standard test parameters for evaluating mycoplasma clearance filters by filter manufacturers and formed a task force to formulate such a consensus among manufacturers. The use of standardized test parameters by filter manufacturers, including the preparation of the culture broth, will facilitate the end user's evaluation of the mycoplasma clearance claims provided by filter vendors. However, it is still important to recognize filter performance will depend on the actual conditions of use; therefore end users should consider, using a risk-based approach, whether process-specific evaluation of filter performance may be warranted for their application. © PDA, Inc. 2014.

Method-independent, Computationally Frugal Convergence Testing for Sensitivity Analysis Techniques

NASA Astrophysics Data System (ADS)

Mai, Juliane; Tolson, Bryan

2017-04-01

The increasing complexity and runtime of environmental models lead to the current situation that the calibration of all model parameters or the estimation of all of their uncertainty is often computationally infeasible. Hence, techniques to determine the sensitivity of model parameters are used to identify most important parameters or model processes. All subsequent model calibrations or uncertainty estimation procedures focus then only on these subsets of parameters and are hence less computational demanding. While the examination of the convergence of calibration and uncertainty methods is state-of-the-art, the convergence of the sensitivity methods is usually not checked. If any, bootstrapping of the sensitivity results is used to determine the reliability of the estimated indexes. Bootstrapping, however, might as well become computationally expensive in case of large model outputs and a high number of bootstraps. We, therefore, present a Model Variable Augmentation (MVA) approach to check the convergence of sensitivity indexes without performing any additional model run. This technique is method- and model-independent. It can be applied either during the sensitivity analysis (SA) or afterwards. The latter case enables the checking of already processed sensitivity indexes. To demonstrate the method independency of the convergence testing method, we applied it to three widely used, global SA methods: the screening method known as Morris method or Elementary Effects (Morris 1991, Campolongo et al., 2000), the variance-based Sobol' method (Solbol' 1993, Saltelli et al. 2010) and a derivative-based method known as Parameter Importance index (Goehler et al. 2013). The new convergence testing method is first scrutinized using 12 analytical benchmark functions (Cuntz & Mai et al. 2015) where the true indexes of aforementioned three methods are known. This proof of principle shows that the method reliably determines the uncertainty of the SA results when different budgets are used for the SA. Subsequently, we focus on the model-independency by testing the frugal method using the hydrologic model mHM (www.ufz.de/mhm) with about 50 model parameters. The results show that the new frugal method is able to test the convergence and therefore the reliability of SA results in an efficient way. The appealing feature of this new technique is the necessity of no further model evaluation and therefore enables checking of already processed (and published) sensitivity results. This is one step towards reliable and transferable, published sensitivity results.

Molecular dynamics of reversible self-healing materials

NASA Astrophysics Data System (ADS)

Madden, Ian; Luijten, Erik

Hydrolyzable polymers have numerous industrial applications as degradable materials. Recent experimental work by Cheng and co-workers has introduced the concept of hindered urea bond (HUB) chemistry to design self-healing systems. Important control parameters are the steric hindrance of the HUB structures, which is used to tune the hydrolytic degradation kinetics, and their density. We employ molecular dynamics simulations of polymeric interfaces to systematically explore the role of these properties in a coarse-grained model, and make direct comparison to experimental data. Our model provides direct insight into the self-healing process, permitting optimization of the control parameters.

In-situ quality monitoring during laser brazing

NASA Astrophysics Data System (ADS)

Ungers, Michael; Fecker, Daniel; Frank, Sascha; Donst, Dmitri; Märgner, Volker; Abels, Peter; Kaierle, Stefan

Laser brazing of zinc coated steel is a widely established manufacturing process in the automotive sector, where high quality requirements must be fulfilled. The strength, impermeablitiy and surface appearance of the joint are particularly important for judging its quality. The development of an on-line quality control system is highly desired by the industry. This paper presents recent works on the development of such a system, which consists of two cameras operating in different spectral ranges. For the evaluation of the system, seam imperfections are created artificially during experiments. Finally image processing algorithms for monitoring process parameters based the captured images are presented.

D-malate production by permeabilized Pseudomonas pseudoalcaligenes; optimization of conversion and biocatalyst productivity.

PubMed

Michielsen, M J; Frielink, C; Wijffels, R H; Tramper, J; Beeftink, H H

2000-04-14

For the development of a continuous process for the production of solid D-malate from a Ca-maleate suspension by permeabilized Pseudomonas pseudoalcaligenes, it is important to understand the effect of appropriate process parameters on the stability and activity of the biocatalyst. Previously, we quantified the effect of product (D-malate2 -) concentration on both the first-order biocatalyst inactivation rate and on the biocatalytic conversion rate. The effects of the remaining process parameters (ionic strength, and substrate and Ca2 + concentration) on biocatalyst activity are reported here. At (common) ionic strengths below 2 M, biocatalyst activity was unaffected. At high substrate concentrations, inhibition occurred. Ca2+ concentration did not affect biocatalyst activity. The kinetic parameters (both for conversion and inactivation) were determined as a function of temperature by fitting the complete kinetic model, featuring substrate inhibition, competitive product inhibition and first-order irreversible biocatalyst inactivation, at different temperatures simultaneously through three extended data sets of substrate concentration versus time. Temperature affected both the conversion and inactivation parameters. The final model was used to calculate the substrate and biocatalyst costs per mmol of product in a continuous system with biocatalyst replenishment and biocatalyst recycling. Despite the effect of temperature on each kinetic parameter separately, the overall effect of temperature on the costs was found to be negligible (between 293 and 308 K). Within pertinent ranges, the sum of the substrate and biocatalyst costs per mmol of product was calculated to decrease with the influent substrate concentration and the residence time. The sum of the costs showed a minimum as a function of the influent biocatalyst concentration.

A real-time multi-channel monitoring system for stem cell culture process.

PubMed

Xicai Yue; Drakakis, E M; Lim, M; Radomska, A; Hua Ye; Mantalaris, A; Panoskaltsis, N; Cass, A

2008-06-01

A novel, up to 128 channels, multi-parametric physiological measurement system suitable for monitoring hematopoietic stem cell culture processes and cell cultures in general is presented in this paper. The system aims to measure in real-time the most important physical and chemical culture parameters of hematopoietic stem cells, including physicochemical parameters, nutrients, and metabolites, in a long-term culture process. The overarching scope of this research effort is to control and optimize the whole bioprocess by means of the acquisition of real-time quantitative physiological information from the culture. The system is designed in a modular manner. Each hardware module can operate as an independent gain programmable, level shift adjustable, 16 channel data acquisition system specific to a sensor type. Up to eight such data acquisition modules can be combined and connected to the host PC to realize the whole system hardware. The control of data acquisition and the subsequent management of data is performed by the system's software which is coded in LabVIEW. Preliminary experimental results presented here show that the system not only has the ability to interface to various types of sensors allowing the monitoring of different types of culture parameters. Moreover, it can capture dynamic variations of culture parameters by means of real-time multi-channel measurements thus providing additional information on both temporal and spatial profiles of these parameters within a bioreactor. The system is by no means constrained in the hematopoietic stem cell culture field only. It is suitable for cell growth monitoring applications in general.

Statistical analysis and optimization of direct metal laser deposition of 227-F Colmonoy nickel alloy

NASA Astrophysics Data System (ADS)

Angelastro, A.; Campanelli, S. L.; Casalino, G.

2017-09-01

This paper presents a study on process parameters and building strategy for the deposition of Colmonoy 227-F powder by CO2 laser with a focal spot diameter of 0.3 mm. Colmonoy 227-F is a nickel alloy especially designed for mold manufacturing. The substrate material is a 10 mm thick plate of AISI 304 steel. A commercial CO2 laser welding machine was equipped with a low-cost powder feeding system. In this work, following another one in which laser power, scanning speed and powder flow rate had been studied, the effects of two important process parameters, i.e. hatch spacing and step height, on the properties of the built parts were analysed. The explored ranges of hatch spacing and step height were respectively 150-300 μm and 100-200 μm, whose dimensions were comparable with that of the laser spot. The roughness, adhesion, microstructure, microhardness and density of the manufactured specimens were studied for multi-layer samples, which were made of 30 layers. The statistical significance of the studied process parameters was assessed by the analysis of the variance. The process parameters used allowed to obtain both first layer-to-substrate and layer-to-layer good adhesions. The microstructure was fine and almost defect-free. The microhardness of the deposited material was about 100 HV higher than that of the starting powder. The density as high as 98% of that of the same bulk alloy was more than satisfactory. Finally, simultaneous optimization of density and roughness was performed using the contour plots.

Changes in water quality parameters due to in-sewer processes.

PubMed

Boxall, J; Shepherd, W; Guymer, I; Fox, K

2003-01-01

Combined sewer systems contain a large number of organic and inorganic pollutants from both domestic and industrial sources. These pollutants are often retained within the combined sewer system for significant lengths of time before entering sewage treatment works, or being spilt to a watercourse via a combined sewer overflow (CSO) during storm conditions. Currently little knowledge exists concerning the effects of in sewer processes on pollutants. Understanding of in-sewer processes is important for the effective and efficient design of treatment works and CSO chambers and for impact assessments on receiving waters. A series of studies covering storm and dry weather flow conditions were undertaken with the aim of investigating the nature of in-sewer processes. These studies consisted of marking a body of water with a fluorescent tracer. The tracer was then monitored at a series of downstream sites, and discrete samples collected from the body of water as it progressed through the sewer. The samples were analysed for water quality parameters and these results investigated in tandem with the detailed hydraulic information gained through the tracer studies. The results highlight the hydraulic differences between storm and dry weather conditions such as increased travel times and mixing under storm conditions. The Advection Dispersion Equation (ADE) and Aggregated Dead Zone (ADZ) model parameters have been quantified for the tracer data. The ADE mixing coefficient is shown to increase by an order of magnitude for storm conditions. The ADZ dispersive fraction parameter is shown to be approximately constant with flow. Chemical reactions and decay within the sewer system were found to be consistent with oxygen limitation.

Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

USGS Publications Warehouse

Rakovec, O.; Hill, Mary C.; Clark, M.P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

2014-01-01

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

Analytical method for determining rill detachment rate of purple soil as compared with that of loess soil

USDA-ARS?s Scientific Manuscript database

Rill detachment is an important process in rill erosion. The rill detachment rate is the fundamental basis for determination of the parameters of a rill erosion model. In this paper, an analytical method was proposed to estimate the rill detachment rate. The method is based on the exact analytical s...

Multi-functional micromotor: microfluidic fabrication and water treatment application.

PubMed

Chen, Anqi; Ge, Xue-Hui; Chen, Jian; Zhang, Liyuan; Xu, Jian-Hong

2017-12-05

Micromotors are important for a wide variety of applications. Here, we develop a microfluidic approach for one-step fabrication of a Janus self-propelled micromotor with multiple functions. By fine tuning the fabrication parameters and loading functional nanoparticles, our micromotor reaches a high speed and achieves an oriented function to promote the water purification efficiency and recycling process.

Use of space for development of commercial plant natural products

NASA Astrophysics Data System (ADS)

Draeger, Norman A.

1997-01-01

Plant experiments conducted in environments where conditions are carefully controlled reveal fundamental information about physiological processes. An important environmental parameter is gravity, the effects of which may be better understood in part through experiments conducted in space. New insights gained can be used to develop commercial plant natural products in industries such as pharmaceuticals and biocontrol.

Minimization of operational impacts on spectrophotometer color measurements for cotton

USDA-ARS?s Scientific Manuscript database

A key cotton quality and processing property that is gaining increasing importance is the color of the cotton. Cotton fiber in the U.S. is classified for color using the Uster® High Volume Instrument (HVI), using the parameters Rd and +b. Rd and +b are specific to cotton fiber and are not typical ...

Regulatory issues for computerized electrocardiographic devices.

PubMed

Muni, Neal I; Ho, Charles; Mallis, Elias

2004-01-01

Computerized electrocardiogram (ECG) devices are regulated in the U.S. by the FDA Center for Devices and Radiological Health (CDRH). This article aims to highlight the salient points of the FDA regulatory review process, including the important distinction between a "tool" claim and a "clinical" claim in the intended use of a computerized ECG device. Specifically, a tool claim relates to the ability of the device to accurately measure a certain ECG parameter, such as T-wave alternans (TWA), while a clinical claim imputes a particular health hazard associated with the identified parameter, such as increased risk of ventricular tachyarrhythmia or sudden death. Given that both types of claims are equally important and receive the same regulatory scrutiny, the manufacturer of a new ECG diagnostic device should consider the distinction and regulatory pathways for approval between the two types of claims discussed in this paper.

A critical literature review of focused electron beam induced deposition

NASA Astrophysics Data System (ADS)

van Dorp, W. F.; Hagen, C. W.

2008-10-01

An extensive review is given of the results from literature on electron beam induced deposition. Electron beam induced deposition is a complex process, where many and often mutually dependent factors are involved. The process has been studied by many over many years in many different experimental setups, so it is not surprising that there is a great variety of experimental results. To come to a better understanding of the process, it is important to see to which extent the experimental results are consistent with each other and with the existing model. All results from literature were categorized by sorting the data according to the specific parameter that was varied (current density, acceleration voltage, scan patterns, etc.). Each of these parameters can have an effect on the final deposit properties, such as the physical dimensions, the composition, the morphology, or the conductivity. For each parameter-property combination, the available data are discussed and (as far as possible) interpreted. By combining models for electron scattering in a solid, two different growth regimes, and electron beam induced heating, the majority of the experimental results were explained qualitatively. This indicates that the physical processes are well understood, although quantitatively speaking the models can still be improved. The review makes clear that several major issues remain. One issue encountered when interpreting results from literature is the lack of data. Often, important parameters (such as the local precursor pressure) are not reported, which can complicate interpretation of the results. Another issue is the fact that the cross section for electron induced dissociation is unknown. In a number of cases, a correlation between the vertical growth rate and the secondary electron yield was found, which suggests that the secondary electrons dominate the dissociation rather than the primary electrons. Conclusive evidence for this hypothesis has not been found. Finally, there is a limited understanding of the mechanism of electron induced precursor dissociation. In many cases, the deposit composition is not directly dependent on the stoichiometric composition of the precursor and the electron induced decomposition paths can be very different from those expected from calculations or thermal decomposition. The dissociation mechanism is one of the key factors determining the purity of the deposits and a better understanding of this process will help develop electron beam induced deposition into a viable nanofabrication technique.

Application of 'Six Sigma{sup TM}' and 'Design of Experiment' for Cementation - Recipe Development for Evaporator Concentrate for NPP Ling AO, Phase II (China) - 12555

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fehrmann, Henning; Perdue, Robert

2012-07-01

Cementation of radioactive waste is a common technology. The waste is mixed with cement and water and forms a stable, solid block. The physical properties like compression strength or low leach ability depends strongly on the cement recipe. Due to the fact that this waste cement mixture has to fulfill special requirements, a recipe development is necessary. The Six Sigma{sup TM}' DMAIC methodology, together with the Design of experiment (DoE) approach, was employed to optimize the process of a recipe development for cementation at the Ling Ao nuclear power plant (NPP) in China. The DMAIC offers a structured, systematical andmore » traceable process to derive test parameters. The DoE test plans and statistical analysis is efficient regarding the amount of test runs and the benefit gain by getting a transfer function. A transfer function enables simulation which is useful to optimize the later process and being responsive to changes. The DoE method was successfully applied for developing a cementation recipe for both evaporator concentrate and resin waste in the plant. The key input parameters were determined, evaluated and the control of these parameters were included into the design. The applied Six Sigma{sup TM} tools can help to organize the thinking during the engineering process. Data are organized and clearly presented. Various variables can be limited to the most important ones. The Six Sigma{sup TM} tools help to make the thinking and decision process trace able. The tools can help to make data driven decisions (e.g. C and E Matrix). But the tools are not the only golden way. Results from scoring tools like the C and E Matrix need close review before using them. The DoE is an effective tool for generating test plans. DoE can be used with a small number of tests runs, but gives a valuable result from an engineering perspective in terms of a transfer function. The DoE prediction results, however, are only valid in the tested area. So a careful selection of input parameter and their limits for setting up a DoE is very important. An extrapolation of results is not recommended because the results are not reliable out of the tested area. (authors)« less

COSP for Windows: Strategies for Rapid Analyses of Cyclic Oxidation Behavior

NASA Technical Reports Server (NTRS)

Smialek, James L.; Auping, Judith V.

2002-01-01

COSP is a publicly available computer program that models the cyclic oxidation weight gain and spallation process. Inputs to the model include the selection of an oxidation growth law and a spalling geometry, plus oxide phase, growth rate, spall constant, and cycle duration parameters. Output includes weight change, the amounts of retained and spalled oxide, the total oxygen and metal consumed, and the terminal rates of weight loss and metal consumption. The present version is Windows based and can accordingly be operated conveniently while other applications remain open for importing experimental weight change data, storing model output data, or plotting model curves. Point-and-click operating features include multiple drop-down menus for input parameters, data importing, and quick, on-screen plots showing one selection of the six output parameters for up to 10 models. A run summary text lists various characteristic parameters that are helpful in describing cyclic behavior, such as the maximum weight change, the number of cycles to reach the maximum weight gain or zero weight change, the ratio of these, and the final rate of weight loss. The program includes save and print options as well as a help file. Families of model curves readily show the sensitivity to various input parameters. The cyclic behaviors of nickel aluminide (NiAl) and a complex superalloy are shown to be properly fitted by model curves. However, caution is always advised regarding the uniqueness claimed for any specific set of input parameters,

Strain localisation in the continental lithosphere, a scale-dependent process

NASA Astrophysics Data System (ADS)

Jolivet, Laurent; Burov, Evguenii

2013-04-01

Strain localisation in continents is a general question tackled by specialists of various disciplines in Earth Sciences. Field geologists working at regional scale are able to describe the succession of events leading to the formation of large strain zones that accommodate large displacement within plate boundaries. On the other end of the spectrum, laboratory experiments provide numbers that quantitatively describe the rheology of rock material at the scale of a few mm and at deformation rates up to 8-10 orders of magnitude faster than in nature. Extrapolating from the scale of the experiment to the scale of the continental lithosphere is a considerable leap across 8-10 orders of magnitude both in space and time. It is however quite obvious that different processes are at work for each scale considered. At the scale of a grain aggregate diffusion within individual grains, dislocation or grain boundary sliding, depending on temperature and fluid conditions, are of primary importance. But at the scale of a mountain belt, a major detachment or a strike-slip shear zone that have accommodated tens or hundreds of kilometres of relative displacement, other parameters will take over such as structural softening and the heterogeneity of the crust inherited from past tectonic events that have juxtaposed rock units of very different compositions and induced a strong orientation of rocks. Once the deformation is localised along major shear zones, grain size reduction, interaction between rocks and fluids and metamorphic reactions and other small-scale processes tend to further localise the strain. Because the crust is colder and more lithologically complex this heterogeneity is likely much more prominent in the crust than in the mantle and then the relative importance of "small-scale" and "large-scale" parameters will be very different in the crust and in the mantle. Thus, depending upon the relative thickness of the crust and mantle in the deforming lithosphere, the role of each mechanism will have more or less important consequences on strain localisation. This complexity sometimes leads to disregard of experimental parameters in large-scale thermo-mechanical models and to use instead ad hoc "large-scale" numbers that better fit the observed geological history. The goal of the ERC RHEOLITH project is to associate to each tectonic process the relevant rheological parameters depending upon the scale considered, in an attempt to elaborate a generalized "Preliminary Rheology Model Set for Lithosphere" (PReMSL), which will cover the entire time and spatial scale range of deformation.

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

NASA Astrophysics Data System (ADS)

He, F.

2015-12-01

This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.

Magnetohydrodynamics effect on convective boundary layer flow and heat transfer of viscoelastic micropolar fluid past a sphere

NASA Astrophysics Data System (ADS)

Amera Aziz, Laila; Kasim, Abdul Rahman Mohd; Zuki Salleh, Mohd; Syahidah Yusoff, Nur; Shafie, Sharidan

2017-09-01

The main interest of this study is to investigate the effect of MHD on the boundary layer flow and heat transfer of viscoelastic micropolar fluid. Governing equations are transformed into dimensionless form in order to reduce their complexity. Then, the stream function is applied to the dimensionless equations to produce partial differential equations which are then solved numerically using the Keller-box method in Fortran programming. The numerical results are compared to published study to ensure the reliability of present results. The effects of selected physical parameters such as the viscoelastic parameter, K, micropolar parameter, K1 and magnetic parameter, M on the flow and heat transfer are discussed and presented in tabular and graphical form. The findings from this study will be of critical importance in the fields of medicine, chemical as well as industrial processes where magnetic field is involved.

Validation of High Displacement Piezoelectric Actuator Finite Element Models

NASA Technical Reports Server (NTRS)

Taleghani, B. K.

2000-01-01

The paper presents the results obtained by using NASTRAN(Registered Trademark) and ANSYS(Regitered Trademark) finite element codes to predict doming of the THUNDER piezoelectric actuators during the manufacturing process and subsequent straining due to an applied input voltage. To effectively use such devices in engineering applications, modeling and characterization are essential. Length, width, dome height, and thickness are important parameters for users of such devices. Therefore, finite element models were used to assess the effects of these parameters. NASTRAN(Registered Trademark) and ANSYS(Registered Trademark) used different methods for modeling piezoelectric effects. In NASTRAN(Registered Trademark), a thermal analogy was used to represent voltage at nodes as equivalent temperatures, while ANSYS(Registered Trademark) processed the voltage directly using piezoelectric finite elements. The results of finite element models were validated by using the experimental results.

Reintrepreting the cardiovascular system as a mechanical model

NASA Astrophysics Data System (ADS)

Lemos, Diogo; Machado, José; Minas, Graça; Soares, Filomena; Barros, Carla; Leão, Celina Pinto

2013-10-01

The simulation of the different physiological systems is very useful as a pedagogical tool, allowing a better understanding of the mechanisms and the functions of the processes. The observation of the physiological phenomena through mechanical simulators represents a great asset. Furthermore, the development of these simulators allows reinterpreting physiological systems, with the advantage of using the same transducers and sensors that are commonly used in diagnostic and therapeutic cardiovascular procedures for the monitoring of system' parameters. The cardiovascular system is one of the most important systems of the human body and has been the target of several biomedical studies. The present work describes a mechanical simulation of the cardiovascular system, in particularly, the systemic circulation, which can be described in terms of its hemodynamic variables. From the mechanical process and parameters, physiological system's behavior was reproduced, as accurately as possible.

Spectroscopic properties of the molecular ions BeX+ (X=Na, K, Rb): forming cold molecular ions from an ion-atom mixture by stimulated Raman adiabatic process

NASA Astrophysics Data System (ADS)

Ladjimi, Hela; Sardar, Dibyendu; Farjallah, Mohamed; Alharzali, Nisrin; Naskar, Somnath; Mlika, Rym; Berriche, Hamid; Deb, Bimalendu

2018-07-01

In this theoretical work, we calculate potential energy curves, spectroscopic parameters and transition dipole moments of molecular ions BeX+ (X=Na, K, Rb) composed of alkaline ion Be and alkali atom X with a quantum chemistry approach based on the pseudopotential model, Gaussian basis sets, effective core polarisation potentials and full configuration interaction. We study in detail collisions of the alkaline ion and alkali atom in quantum regime. Besides, we study the possibility of the formation of molecular ions from the ion-atom colliding systems by stimulated Raman adiabatic process and discuss the parameters regime under which the population transfer is feasible. Our results are important for ion-atom cold collisions and experimental realisation of cold molecular ion formation.

High speed demodulation systems for fiber optic grating sensors

NASA Technical Reports Server (NTRS)

Udd, Eric (Inventor); Weisshaar, Andreas (Inventor)

2002-01-01

Fiber optic grating sensor demodulation systems are described that offer high speed and multiplexing options for both single and multiple parameter fiber optic grating sensors. To attain very high speeds for single parameter fiber grating sensors ratio techniques are used that allow a series of sensors to be placed in a single fiber while retaining high speed capability. These methods can be extended to multiparameter fiber grating sensors. Optimization of speeds can be obtained by minimizing the number of spectral peaks that must be processed and it is shown that two or three spectral peak measurements may in specific multiparameter applications offer comparable or better performance than processing four spectral peaks. Combining the ratio methods with minimization of peak measurements allows very high speed measurement of such important environmental effects as transverse strain and pressure.

Towards simplification of hydrologic modeling: Identification of dominant processes

USGS Publications Warehouse

Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.

2016-01-01

The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

Geometric parameters determination of the installation for oil-contaminated soils decontamination in Russia, the Siberian region and the Arctic zones climatic conditions with reagent encapsulating

NASA Astrophysics Data System (ADS)

Shtripling, L. O.; Kholkin, E. G.

2018-01-01

The article presents the procedure for determining the basic geometrical setting parameters for the oil-contaminated soils decontamination with reagent encapsulation method. An installation is considered for the operational elimination of the emergency consequences accompanied with oil spills, and the installation is adapted to winter conditions. In the installations exothermic process thermal energy of chemical neutralization of oil-contaminated soils released during the decontamination is used to thaw frozen subsequent portions of oil-contaminated soil. Installation for oil-contaminated soil decontamination as compared with other units has an important advantage, and it is, if necessary (e.g., in winter) in using the heat energy released at each decontamination process stage of oil-contaminated soil, in normal conditions the heat is dispersed into the environment. In addition, the short-term forced carbon dioxide delivery at the decontamination process final stage to a high concentration directly into the installation allows replacing the long process of microcapsule shells formation and hardening that occur in natural conditions in the open air.

Implementation of quality by design approach in manufacturing process optimization of dry granulated, immediate release, coated tablets - a case study.

PubMed

Teżyk, Michał; Jakubowska, Emilia; Milanowski, Bartłomiej; Lulek, Janina

2017-10-01

The aim of this study was to optimize the process of tablets compression and identification of film-coating critical process parameters (CPPs) affecting critical quality attributes (CQAs) using quality by design (QbD) approach. Design of experiment (DOE) and regression methods were employed to investigate hardness, disintegration time, and thickness of uncoated tablets depending on slugging and tableting compression force (CPPs). Plackett-Burman experimental design was applied to identify critical coating process parameters among selected ones that is: drying and preheating time, atomization air pressure, spray rate, air volume, inlet air temperature, and drum pressure that may influence the hardness and disintegration time of coated tablets. As a result of the research, design space was established to facilitate an in-depth understanding of existing relationship between CPPs and CQAs of intermediate product (uncoated tablets). Screening revealed that spray rate and inlet air temperature are two most important factors that affect the hardness of coated tablets. Simultaneously, none of the tested coating factors have influence on disintegration time. The observation was confirmed by conducting film coating of pilot size batches.

Infrared thermography of welding zones produced by polymer extrusion additive manufacturing✩

PubMed Central

Seppala, Jonathan E.; Migler, Kalman D.

2016-01-01

In common thermoplastic additive manufacturing (AM) processes, a solid polymer filament is melted, extruded though a rastering nozzle, welded onto neighboring layers and solidified. The temperature of the polymer at each of these stages is the key parameter governing these non-equilibrium processes, but due to its strong spatial and temporal variations, it is difficult to measure accurately. Here we utilize infrared (IR) imaging - in conjunction with necessary reflection corrections and calibration procedures - to measure these temperature profiles of a model polymer during 3D printing. From the temperature profiles of the printed layer (road) and sublayers, the temporal profile of the crucially important weld temperatures can be obtained. Under typical printing conditions, the weld temperature decreases at a rate of approximately 100 °C/s and remains above the glass transition temperature for approximately 1 s. These measurement methods are a first step in the development of strategies to control and model the printing processes and in the ability to develop models that correlate critical part strength with material and processing parameters. PMID:29167755

Infrared thermography of welding zones produced by polymer extrusion additive manufacturing.

PubMed

Seppala, Jonathan E; Migler, Kalman D

2016-10-01

In common thermoplastic additive manufacturing (AM) processes, a solid polymer filament is melted, extruded though a rastering nozzle, welded onto neighboring layers and solidified. The temperature of the polymer at each of these stages is the key parameter governing these non-equilibrium processes, but due to its strong spatial and temporal variations, it is difficult to measure accurately. Here we utilize infrared (IR) imaging - in conjunction with necessary reflection corrections and calibration procedures - to measure these temperature profiles of a model polymer during 3D printing. From the temperature profiles of the printed layer (road) and sublayers, the temporal profile of the crucially important weld temperatures can be obtained. Under typical printing conditions, the weld temperature decreases at a rate of approximately 100 °C/s and remains above the glass transition temperature for approximately 1 s. These measurement methods are a first step in the development of strategies to control and model the printing processes and in the ability to develop models that correlate critical part strength with material and processing parameters.

Evaluation of a new parallel numerical parameter optimization algorithm for a dynamical system

NASA Astrophysics Data System (ADS)

Duran, Ahmet; Tuncel, Mehmet

2016-10-01

It is important to have a scalable parallel numerical parameter optimization algorithm for a dynamical system used in financial applications where time limitation is crucial. We use Message Passing Interface parallel programming and present such a new parallel algorithm for parameter estimation. For example, we apply the algorithm to the asset flow differential equations that have been developed and analyzed since 1989 (see [3-6] and references contained therein). We achieved speed-up for some time series to run up to 512 cores (see [10]). Unlike [10], we consider more extensive financial market situations, for example, in presence of low volatility, high volatility and stock market price at a discount/premium to its net asset value with varying magnitude, in this work. Moreover, we evaluated the convergence of the model parameter vector, the nonlinear least squares error and maximum improvement factor to quantify the success of the optimization process depending on the number of initial parameter vectors.

Rendering of HDR content on LDR displays: an objective approach

NASA Astrophysics Data System (ADS)

Krasula, Lukáš; Narwaria, Manish; Fliegel, Karel; Le Callet, Patrick

2015-09-01

Dynamic range compression (or tone mapping) of HDR content is an essential step towards rendering it on traditional LDR displays in a meaningful way. This is however non-trivial and one of the reasons is that tone mapping operators (TMOs) usually need content-specific parameters to achieve the said goal. While subjective TMO parameter adjustment is the most accurate, it may not be easily deployable in many practical applications. Its subjective nature can also influence the comparison of different operators. Thus, there is a need for objective TMO parameter selection to automate the rendering process. To that end, we investigate into a new objective method for TMO parameters optimization. Our method is based on quantification of contrast reversal and naturalness. As an important advantage, it does not require any prior knowledge about the input HDR image and works independently on the used TMO. Experimental results using a variety of HDR images and several popular TMOs demonstrate the value of our method in comparison to default TMO parameter settings.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process.

PubMed

Deng, Bo; Shi, Yaoyao; Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-31

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

PubMed Central

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

Study the Effect of SiO2 Based Flux on Dilution in Submerged Arc Welding

NASA Astrophysics Data System (ADS)

kumar, Aditya; Maheshwari, Sachin

2017-08-01

This paper highlights the method for prediction of dilution in submerged arc welding (SAW). The most important factors of weld bead geometry are governed by the weld dilution which controls the chemical and mechanical properties. Submerged arc welding process is used generally due to its very easy control of process variables, good penetration, high weld quality, and smooth finish. Machining parameters, with suitable weld quality can be achieved with the different composition of the flux in the weld. In the present study Si02-Al2O3-CaO flux system was used. In SiO2 based flux NiO, MnO, MgO were mixed in various proportions. The paper investigates the relationship between the process parameters like voltage, % of flux constituents and dilution with the help of Taguchi’s method. The experiments were designed according to Taguchi L9 orthogonal array, while varying the voltage at two different levels in addition to alloying elements. Then the optimal results conditions were verified by confirmatory experiments.

Stability of auditory discrimination and novelty processing in physiological aging.

PubMed

Raggi, Alberto; Tasca, Domenica; Rundo, Francesco; Ferri, Raffaele

2013-01-01

Complex higher-order cognitive functions and their possible changes with aging are mandatory objectives of cognitive neuroscience. Event-related potentials (ERPs) allow investigators to probe the earliest stages of information processing. N100, Mismatch negativity (MMN) and P3a are auditory ERP components that reflect automatic sensory discrimination. The aim of the present study was to determine if N100, MMN and P3a parameters are stable in healthy aged subjects, compared to those of normal young adults. Normal young adults and older participants were assessed using standardized cognitive functional instruments and their ERPs were obtained with an auditory stimulation at two different interstimulus intervals, during a passive paradigm. All individuals were within the normal range on cognitive tests. No significant differences were found for any ERP parameters obtained from the two age groups. This study shows that aging is characterized by a stability of the auditory discrimination and novelty processing. This is important for the arrangement of normative for the detection of subtle preclinical changes due to abnormal brain aging.

Chemical and Physical Soil Restoration in Mining Areas

NASA Astrophysics Data System (ADS)

Teresinha Gonçalves Bizuti, Denise; de Marchi Soares, Thaís; Roberti Alves de Almeida, Danilo; Sartorio, Simone Daniela; Casagrande, José Carlos; Santin Brancalion, Pedro Henrique

2017-04-01

The current trend of ecological restoration is to address the recovery of degraded areas by ecosystemic way, overcoming the rehabilitation process. In this sense, the topsoil and other complementary techniques in mining areas plays an important role in soil recovery. The aim of this study was to contextualize the soil improvement, with the use of topsoil through chemical and physical attributes, relative to secondary succession areas in restoration, as well as in reference ecosystems (natural forest). Eighteen areas were evaluated, six in forest restoration process, six native forests and six just mining areas. The areas were sampled in the depths of 0-5, 5-10, 10-20, 20-40 and 40-60 cm. Chemical indicators measured were parameters of soil fertility and texture, macroporosity, microporosity, density and total porosity as physical parameters. The forest restoration using topsoil was effective in triggering a process of soil recovery, promoting, in seven years, chemical and physical characteristics similar to those of the reference ecosystem.

Estimation of Kubo number and correlation length of fluctuating magnetic fields and pressure in BOUT + + edge pedestal collapse simulation

NASA Astrophysics Data System (ADS)

Kim, Jaewook; Lee, W.-J.; Jhang, Hogun; Kaang, H. H.; Ghim, Y.-C.

2017-10-01

Stochastic magnetic fields are thought to be as one of the possible mechanisms for anomalous transport of density, momentum and heat across the magnetic field lines. Kubo number and Chirikov parameter are quantifications of the stochasticity, and previous studies show that perpendicular transport strongly depends on the magnetic Kubo number (MKN). If MKN is smaller than one, diffusion process will follow Rechester-Rosenbluth model; whereas if it is larger than one, percolation theory dominates the diffusion process. Thus, estimation of Kubo number plays an important role to understand diffusion process caused by stochastic magnetic fields. However, spatially localized experimental measurement of fluctuating magnetic fields in a tokamak is difficult, and we attempt to estimate MKNs using BOUT + + simulation data with pedestal collapse. In addition, we calculate correlation length of fluctuating pressures and Chirikov parameters to investigate variation correlation lengths in the simulation. We, then, discuss how one may experimentally estimate MKNs.

ON THE DEGREE OF CONVERSION AND COEFFICIENT OF THERMAL EXPANSION OF A SINGLE FIBER COMPOSITE USING A FBG SENSOR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lai, M.; Botsis, J.; Coric, D.

2008-08-28

The increasing needs of extending the lifetime in high-technology fields, such as space and aerospace, rail transport and naval systems, require quality enhancing of the composite materials either from a processing standing point or in the sense of resistance to service conditions. It is well accepted that the final quality of composite materials and structures is strongly influenced by processing parameters like curing and post-curing temperatures, rate of heating and cooling, applied vacuum, etc. To optimize manufacturing cycles, residual strains evolution due to chemical shrinkage and other physical parameters of the constituent materials must be characterized in situ. Such knowledgemore » can lead to a sensible reduction in defects and to improved physical and mechanical properties of final products. In this context continuous monitoring of strains distribution developed during processing is important in understanding and retrieving components' and materials' characteristics such as local strains gradients, degree of curing, coefficient of thermal expansion, moisture absorption, etc.« less

Ceramization of low and intermediate level radioactive wastes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fiquet, O.; Berson, X.

1993-12-31

A ceramic conditioning is studied for a large variety of low and intermediate level wastes. These wastes arise from several waste streams coming from all process steps of the fuel cycle. The physical properties of ceramics can advantageously be used for radioactive waste immobilization. Their chemical durability can offer a barrier against external aggression. More over, some minerals have possible host sites in their crystal structure for heavy elements which can confer the best immobilization mechanism. The general route for development studies is described giving compositions and process choices. Investigations have been conducted on clay materials and on the processmore » parameters which condition the final product properties. Two practical examples are described concerning chemical precipitation sludge resulting from liquid waste treatment and chamot used as a fluidized bed in a graphite incinerator. Important process parameters are put in evidence and the possibility of a pilot plant development is briefly mentioned. Results of investigations are promising to define a new route of conditioning.« less

Influences of growth parameters on the reaction pathway during GaN synthesis

NASA Astrophysics Data System (ADS)

Zhang, Zhi; Liu, Zhongyi; Fang, Haisheng

2018-01-01

Gallium nitride (GaN) film growth is a complicated physical and chemical process including fluid flow, heat transfer, species transport and chemical reaction. Study of the reaction mechanism, i.e., the reaction pathway, is important for optimizing the growth process in the actual manufacture. In the paper, the growth pathway of GaN in a closed-coupled showerhead metal-organic chemical vapor deposition (CCS-MOCVD) reactor is investigated in detail using computational fluid dynamics (CFD). Influences of the process parameters, such as the chamber pressure, the inlet temperature, the susceptor temperature and the pre-exponential factor, on the reaction pathway are examined. The results show that increases of the chamber pressure or the inlet temperature, as well as reductions of the susceptor temperature or the pre-exponential factor lead to the adduct route dominating the growth. The deposition rate contributed by the decomposition route, however, can be enhanced dramatically by increasing the inlet temperature, the susceptor temperature and the pre-exponential factor.

Highly Segmented Thermal Barrier Coatings Deposited by Suspension Plasma Spray: Effects of Spray Process on Microstructure

NASA Astrophysics Data System (ADS)

Chen, Xiaolong; Honda, Hiroshi; Kuroda, Seiji; Araki, Hiroshi; Murakami, Hideyuki; Watanabe, Makoto; Sakka, Yoshio

2016-12-01

Effects of the ceramic powder size used for suspension as well as several processing parameters in suspension plasma spraying of YSZ were investigated experimentally, aiming to fabricate highly segmented microstructures for thermal barrier coating (TBC) applications. Particle image velocimetry (PIV) was used to observe the atomization process and the velocity distribution of atomized droplets and ceramic particles travelling toward the substrates. The tested parameters included the secondary plasma gas (He versus H2), suspension injection flow rate, and substrate surface roughness. Results indicated that a plasma jet with a relatively higher content of He or H2 as the secondary plasma gas was critical to produce highly segmented YSZ TBCs with a crack density up to 12 cracks/mm. The optimized suspension flow rate played an important role to realize coatings with a reduced porosity level and improved adhesion. An increased powder size and higher operation power level were beneficial for the formation of highly segmented coatings onto substrates with a wider range of surface roughness.

Design and implementation of a cloud based lithography illumination pupil processing application

NASA Astrophysics Data System (ADS)

Zhang, Youbao; Ma, Xinghua; Zhu, Jing; Zhang, Fang; Huang, Huijie

2017-02-01

Pupil parameters are important parameters to evaluate the quality of lithography illumination system. In this paper, a cloud based full-featured pupil processing application is implemented. A web browser is used for the UI (User Interface), the websocket protocol and JSON format are used for the communication between the client and the server, and the computing part is implemented in the server side, where the application integrated a variety of high quality professional libraries, such as image processing libraries libvips and ImageMagic, automatic reporting system latex, etc., to support the program. The cloud based framework takes advantage of server's superior computing power and rich software collections, and the program could run anywhere there is a modern browser due to its web UI design. Compared to the traditional way of software operation model: purchased, licensed, shipped, downloaded, installed, maintained, and upgraded, the new cloud based approach, which is no installation, easy to use and maintenance, opens up a new way. Cloud based application probably is the future of the software development.

Characterization of Developer Application Methods Used in Fluorescent Penetrant Inspection

NASA Astrophysics Data System (ADS)

Brasche, L. J. H.; Lopez, R.; Eisenmann, D.

2006-03-01

Fluorescent penetrant inspection (FPI) is the most widely used inspection method for aviation components seeing use for production as well as an inservice inspection applications. FPI is a multiple step process requiring attention to the process parameters for each step in order to enable a successful inspection. A multiyear program is underway to evaluate the most important factors affecting the performance of FPI, to determine whether existing industry specifications adequately address control of the process parameters, and to provide the needed engineering data to the public domain. The final step prior to the inspection is the application of developer with typical aviation inspections involving the use of dry powder (form d) usually applied using either a pressure wand or dust storm chamber. Results from several typical dust storm chambers and wand applications have shown less than optimal performance. Measurements of indication brightness and recording of the UVA image, and in some cases, formal probability of detection (POD) studies were used to assess the developer application methods. Key conclusions and initial recommendations are provided.

Offline modeling for product quality prediction of mineral processing using modeling error PDF shaping and entropy minimization.

PubMed

Ding, Jinliang; Chai, Tianyou; Wang, Hong

2011-03-01

This paper presents a novel offline modeling for product quality prediction of mineral processing which consists of a number of unit processes in series. The prediction of the product quality of the whole mineral process (i.e., the mixed concentrate grade) plays an important role and the establishment of its predictive model is a key issue for the plantwide optimization. For this purpose, a hybrid modeling approach of the mixed concentrate grade prediction is proposed, which consists of a linear model and a nonlinear model. The least-squares support vector machine is adopted to establish the nonlinear model. The inputs of the predictive model are the performance indices of each unit process, while the output is the mixed concentrate grade. In this paper, the model parameter selection is transformed into the shape control of the probability density function (PDF) of the modeling error. In this context, both the PDF-control-based and minimum-entropy-based model parameter selection approaches are proposed. Indeed, this is the first time that the PDF shape control idea is used to deal with system modeling, where the key idea is to turn model parameters so that either the modeling error PDF is controlled to follow a target PDF or the modeling error entropy is minimized. The experimental results using the real plant data and the comparison of the two approaches are discussed. The results show the effectiveness of the proposed approaches.

Preferential flow across scales: how important are plot scale processes for a catchment scale model?

NASA Astrophysics Data System (ADS)

Glaser, Barbara; Jackisch, Conrad; Hopp, Luisa; Klaus, Julian

2017-04-01

Numerous experimental studies showed the importance of preferential flow for solute transport and runoff generation. As a consequence, various approaches exist to incorporate preferential flow in hydrological models. However, few studies have applied models that incorporate preferential flow at hillslope scale and even fewer at catchment scale. Certainly, one main difficulty for progress is the determination of an adequate parameterization for preferential flow at these spatial scales. This study applies a 3D physically based model (HydroGeoSphere) of a headwater region (6 ha) of the Weierbach catchment (Luxembourg). The base model was implemented without preferential flow and was limited in simulating fast catchment responses. Thus we hypothesized that the discharge performance can be improved by utilizing a dual permeability approach for a representation of preferential flow. We used the information of bromide irrigation experiments performed on three 1m2 plots to parameterize preferential flow. In a first step we ran 20.000 Monte Carlo simulations of these irrigation experiments in a 1m2 column of the headwater catchment model, varying the dual permeability parameters (15 variable parameters). These simulations identified many equifinal, yet very different parameter sets that reproduced the bromide depth profiles well. Therefore, in the next step we chose 52 parameter sets (the 40 best and 12 low performing sets) for testing the effect of incorporating preferential flow in the headwater catchment scale model. The variability of the flow pattern responses at the headwater catchment scale was small between the different parameterizations and did not coincide with the variability at plot scale. The simulated discharge time series of the different parameterizations clustered in six groups of similar response, ranging from nearly unaffected to completely changed responses compared to the base case model without dual permeability. Yet, in none of the groups the simulated discharge response clearly improved compared to the base case. Same held true for some observed soil moisture time series, although at plot scale the incorporation of preferential flow was necessary to simulate the irrigation experiments correctly. These results rejected our hypothesis and open a discussion on how important plot scale processes and heterogeneities are at catchment scale. Our preliminary conclusion is that vertical preferential flow is important for the irrigation experiments at the plot scale, while discharge generation at the catchment scale is largely controlled by lateral preferential flow. The lateral component, however, was already considered in the base case model with different hydraulic conductivities in different soil layers. This can explain why the internal behavior of the model at single spots seems not to be relevant for the overall hydrometric catchment response. Nonetheless, the inclusion of vertical preferential flow improved the realism of internal processes of the model (fitting profiles at plot scale, unchanged response at catchment scale) and should be considered depending on the intended use of the model. Furthermore, we cannot exclude with certainty yet that the quantitative discharge performance at catchment scale cannot be improved by utilizing a dual permeability approach, which will be tested in parameter optimization process.

Volta phase plate data collection facilitates image processing and cryo-EM structure determination.

PubMed

von Loeffelholz, Ottilie; Papai, Gabor; Danev, Radostin; Myasnikov, Alexander G; Natchiar, S Kundhavai; Hazemann, Isabelle; Ménétret, Jean-François; Klaholz, Bruno P

2018-06-01

A current bottleneck in structure determination of macromolecular complexes by cryo electron microscopy (cryo-EM) is the large amount of data needed to obtain high-resolution 3D reconstructions, including through sorting into different conformations and compositions with advanced image processing. Additionally, it may be difficult to visualize small ligands that bind in sub-stoichiometric levels. Volta phase plates (VPP) introduce a phase shift in the contrast transfer and drastically increase the contrast of the recorded low-dose cryo-EM images while preserving high frequency information. Here we present a comparative study to address the behavior of different data sets during image processing and quantify important parameters during structure refinement. The automated data collection was done from the same human ribosome sample either as a conventional defocus range dataset or with a Volta phase plate close to focus (cfVPP) or with a small defocus (dfVPP). The analysis of image processing parameters shows that dfVPP data behave more robustly during cryo-EM structure refinement because particle alignments, Euler angle assignments and 2D & 3D classifications behave more stably and converge faster. In particular, less particle images are required to reach the same resolution in the 3D reconstructions. Finally, we find that defocus range data collection is also applicable to VPP. This study shows that data processing and cryo-EM map interpretation, including atomic model refinement, are facilitated significantly by performing VPP cryo-EM, which will have an important impact on structural biology. Copyright © 2018 Elsevier Inc. All rights reserved.

Optimization of porthole die geometrical variables by Taguchi method

NASA Astrophysics Data System (ADS)

Gagliardi, F.; Ciancio, C.; Ambrogio, G.; Filice, L.

2017-10-01

Porthole die extrusion is commonly used to manufacture hollow profiles made of lightweight alloys for numerous industrial applications. The reliability of extruded parts is affected strongly by the quality of the longitudinal and transversal seam welds. According to that, the die geometry must be designed correctly and the process parameters must be selected properly to achieve the desired product quality. In this study, numerical 3D simulations have been created and run to investigate the role of various geometrical variables on punch load and maximum pressure inside the welding chamber. These are important outputs to take into account affecting, respectively, the necessary capacity of the extrusion press and the quality of the welding lines. The Taguchi technique has been used to reduce the number of the required numerical simulations necessary for considering the influence of twelve different geometric variables. Moreover, the Analysis of variance (ANOVA) has been implemented to individually analyze the effect of each input parameter on the two responses. Then, the methodology has been utilized to determine the optimal process configuration individually optimizing the two investigated process outputs. Finally, the responses of the optimized parameters have been verified through finite element simulations approximating the predicted value closely. This study shows the feasibility of the Taguchi technique for predicting performance, optimization and therefore for improving the design of a porthole extrusion process.

The Art and Science of Climate Model Tuning

DOE PAGES

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew; ...

2017-03-31

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

Modeling Physiological Processes That Relate Toxicant Exposure and Bacterial Population Dynamics

PubMed Central

Klanjscek, Tin; Nisbet, Roger M.; Priester, John H.; Holden, Patricia A.

2012-01-01

Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB) theory, can link physiological processes to microbial growth. Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS). Extensions considered are: (i) additional terms in the equation for the “hazard rate” that quantifies mortality risk; (ii) a variable representing environmental degradation; (iii) a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels; (iv) a new representation of the “lag time” based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd)/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd)/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory. PMID:22328915

The Art and Science of Climate Model Tuning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

Modelling of dynamic contact length in rail grinding process

NASA Astrophysics Data System (ADS)

Zhi, Shaodan; Li, Jianyong; Zarembski, A. M.

2014-09-01

Rails endure frequent dynamic loads from the passing trains for supporting trains and guiding wheels. The accumulated stress concentrations will cause the plastic deformation of rail towards generating corrugations, contact fatigue cracks and also other defects, resulting in more dangerous status even the derailment risks. So the rail grinding technology has been invented with rotating grinding stones pressed on the rail with defects removal. Such rail grinding works are directed by experiences rather than scientifically guidance, lacking of flexible and scientific operating methods. With grinding control unit holding the grinding stones, the rail grinding process has the characteristics not only the surface grinding but also the running railway vehicles. First of all, it's important to analyze the contact length between the grinding stone and the rail, because the contact length is a critical parameter to measure the grinding capabilities of stones. Moreover, it's needed to build up models of railway vehicle unit bonded with the grinding stone to represent the rail grinding car. Therefore the theoretical model for contact length is developed based on the geometrical analysis. And the calculating models are improved considering the grinding car's dynamic behaviors during the grinding process. Eventually, results are obtained based on the models by taking both the operation parameters and the structure parameters into the calculation, which are suitable for revealing the process of rail grinding by combining the grinding mechanism and the railway vehicle systems.

Study on influence of Surface roughness of Ni-Al2O3 nano composite coating and evaluation of wear characteristics

NASA Astrophysics Data System (ADS)

Raghavendra, C. R.; Basavarajappa, S.; Sogalad, Irappa

2018-02-01

Electrodeposition is one of the most technologically feasible and economically superior techniques for producing metallic coating. The advancement in the application of nano particles has grabbed the attention in all fields of engineering. In this present study an attempt has been made on the Ni-Al2O3nano particle composite coating on aluminium substrate by electrodeposition process. The aluminium surface requires a specific pre-treatment for better adherence of coating. In light of this a thin zinc layer is coated on the aluminium substrate by electroless process. In addition to this surface roughness is an important parameter for any coating method and material. In this work Ni-Al2O3 composite coating were successfully coated by varying the process parameters such as bath temperature, current density and particle loading. The experimentation was performed using central composite design based 20 trials of experiments. The effect of process parameters and surface roughness before and after coating is analyzed on wear rate and coating thickness. The results shown a better wear resistance of Ni-Al2O3 composite electrodeposited coating compared to Ni coating. The particle loading and interaction effect of current density with temperature has greater significant effect on wear rate. The surface roughness is significantly affected the wear behaviour and thickness of coating.

Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation

DOE PAGES

Yang, Ben; Zhang, Yaocun; Qian, Yun; ...

2014-03-26

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian Summer Monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved.more » The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. Lastly, by using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.« less

Developing a scalable model of recombinant protein yield from Pichia pastoris: the influence of culture conditions, biomass and induction regime

PubMed Central

Holmes, William J; Darby, Richard AJ; Wilks, Martin DB; Smith, Rodney; Bill, Roslyn M

2009-01-01

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time. PMID:19570229

Metallicity Distribution of Disk Stars and the Formation History of the Milky Way

NASA Astrophysics Data System (ADS)

Toyouchi, Daisuke; Chiba, Masashi

2018-03-01

We investigate the formation history of the stellar disk component in the Milky Way (MW) based on our new chemical evolution model. Our model considers several fundamental baryonic processes, including gas infall, reaccretion of outflowing gas, and radial migration of disk stars. Each of these baryonic processes in the disk evolution is characterized by model parameters that are determined by fitting to various observational data of the stellar disk in the MW, including the radial dependence of the metallicity distribution function (MDF) of the disk stars, which has recently been derived in the APOGEE survey. We succeeded to obtain the best set of model parameters that well reproduces the observed radial dependences of the mean, standard deviation, skewness, and kurtosis of the MDFs for the disk stars. We analyze the basic properties of our model results in detail to gain new insights into the important baryonic processes in the formation history of the MW. One of the remarkable findings is that outflowing gas, containing many heavy elements, preferentially reaccretes onto the outer disk parts, and this recycling process of metal-enriched gas is a key ingredient for reproducing the observed narrower MDFs at larger radii. Moreover, important implications for the radial dependence of gas infall and the influence of radial migration on the MDFs are also inferred from our model calculation. Thus, the MDF of disk stars is a useful clue for studying the formation history of the MW.

A case study: application of statistical process control tool for determining process capability and sigma level.

PubMed

Chopra, Vikram; Bairagi, Mukesh; Trivedi, P; Nagar, Mona

2012-01-01

Statistical process control is the application of statistical methods to the measurement and analysis of variation process. Various regulatory authorities such as Validation Guidance for Industry (2011), International Conference on Harmonisation ICH Q10 (2009), the Health Canada guidelines (2009), Health Science Authority, Singapore: Guidance for Product Quality Review (2008), and International Organization for Standardization ISO-9000:2005 provide regulatory support for the application of statistical process control for better process control and understanding. In this study risk assessments, normal probability distributions, control charts, and capability charts are employed for selection of critical quality attributes, determination of normal probability distribution, statistical stability, and capability of production processes, respectively. The objective of this study is to determine tablet production process quality in the form of sigma process capability. By interpreting data and graph trends, forecasting of critical quality attributes, sigma process capability, and stability of process were studied. The overall study contributes to an assessment of process at the sigma level with respect to out-of-specification attributes produced. Finally, the study will point to an area where the application of quality improvement and quality risk assessment principles for achievement of six sigma-capable processes is possible. Statistical process control is the most advantageous tool for determination of the quality of any production process. This tool is new for the pharmaceutical tablet production process. In the case of pharmaceutical tablet production processes, the quality control parameters act as quality assessment parameters. Application of risk assessment provides selection of critical quality attributes among quality control parameters. Sequential application of normality distributions, control charts, and capability analyses provides a valid statistical process control study on process. Interpretation of such a study provides information about stability, process variability, changing of trends, and quantification of process ability against defective production. Comparative evaluation of critical quality attributes by Pareto charts provides the least capable and most variable process that is liable for improvement. Statistical process control thus proves to be an important tool for six sigma-capable process development and continuous quality improvement.

Laboratory Studies of Homogeneous and Heterogeneous Chemical Processes of Importance in the Upper Atmosphere

NASA Technical Reports Server (NTRS)

Molina, Mario J.

2001-01-01

The objective of this study is to conduct measurements of chemical kinetics parameters for reactions of importance in the stratosphere and upper troposphere, and to study the interaction of trace gases such as HCl with ice surfaces in order to elucidate the mechanism of heterogeneous chlorine activation processes, using both a theoretical and an experimental approach. The measurements will be carried out under temperature and pressure conditions covering those applicable to the stratosphere and upper troposphere. The techniques to be employed include turbulent flow - chemical ionization mass spectrometry, and optical ellipsometry. The next section summarizes our research activities during the second year of the project, and the section that follows consists of the statement of work for the third year.

Determination of the natural convection coefficient in low-gravity

NASA Technical Reports Server (NTRS)

Goldmeer, J.; Motevalli, V.; Haghdoust, M.; Jumper, G.

1992-01-01

Fire safety is an important issue in the current space program; ignition in low-g needs to be studied. The reduction in the gravitational acceleration causes changes in the ignition process. This paper examines the effect of gravity on natural convection, which is one of the important parameters in the ignition process. The NASA-Lewis 2.2 Second Drop Tower provided the low-gravity environment for the experiments. A series of experiments was conducted to measure the temperature of a small copper plate which was heated by a high intensity lamp. These experiments verified that in low-gravity the plate temperature increased faster than in the corresponding 1-g cases, and that the natural convection coefficient rapidly decreased in the low-gravity environment.

Rotor Wake Vortex Definition: Initial Evaluation of 3-C PIV Results of the Hart-II Study

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; vanderWall, Berend; Richard, Hughes; Raffel, Markus; Beaumier, Philippe; Delrieux, Yves; Lim, Joon W.; Yu, Yung H.; Tung, Chee

2002-01-01

An initial evaluation is made of extensive three-component (3C) particle image velocimetry (PIV) measurements within the wake across a rotor disk plane. The model is a 40 percent scale BO-105 helicopter main rotor in forward flight simulation. This study is part of the HART II test program conducted in the German-Dutch Wind Tunnel (DNW). Included are wake vortex field measurements over the advancing and retreating sides of the rotor operating at a typical descent landing condition important for impulsive blade-vortex interaction (BVI) noise. Also included are advancing side results for rotor angle variations from climb to steep descent. Using detailed PIV vector maps of the vortex fields, methods of extracting key vortex parameters are examined and a new method was developed and evaluated. An objective processing method, involving a center-of-vorticity criterion and a vorticity 'disk' integration, was used to determine vortex core size, strength, core velocity distribution characteristics, and unsteadiness. These parameters are mapped over the rotor disk and offer unique physical insight for these parameters of importance for rotor noise and vibration prediction.

Optimal Energy Consumption Analysis of Natural Gas Pipeline

PubMed Central

Liu, Enbin; Li, Changjun; Yang, Yi

2014-01-01

There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent. PMID:24955410

Adaptive control: Myths and realities

NASA Technical Reports Server (NTRS)

Athans, M.; Valavani, L.

1984-01-01

It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.

Investigating the Effect of Cosmic Opacity on Standard Candles

NASA Astrophysics Data System (ADS)

Hu, J.; Yu, H.; Wang, F. Y.

2017-02-01

Standard candles can probe the evolution of dark energy over a large redshift range. But the cosmic opacity can degrade the quality of standard candles. In this paper, we use the latest observations, including Type Ia supernovae (SNe Ia) from the “joint light-curve analysis” sample and Hubble parameters, to probe the opacity of the universe. A joint fitting of the SNe Ia light-curve parameters, cosmological parameters, and opacity is used in order to avoid the cosmological dependence of SNe Ia luminosity distances. The latest gamma-ray bursts are used in order to explore the cosmic opacity at high redshifts. The cosmic reionization process is considered at high redshifts. We find that the sample supports an almost transparent universe for flat ΛCDM and XCDM models. Meanwhile, free electrons deplete photons from standard candles through (inverse) Compton scattering, which is known as an important component of opacity. This Compton dimming may play an important role in future supernova surveys. From analysis, we find that about a few per cent of the cosmic opacity is caused by Compton dimming in the two models, which can be corrected.